Category Big Data, Cloud, BI

Side Hustle Ideas for Experienced Data Scientists in 2022

Side Hustle Ideas for Experienced Data Scientists in 2022

Are you a data scientist? You might be missing out on some opportunities to make money from it. Even if you already have a full-time job in data science, you will be able to leverage your expertise as a big data expert to make extra money on the side.

If you’re feeling strapped for cash and feel like you can earn more money with your knowledge and skills, then starting a side hustle in 2022 is an excellent idea. Everyone has the chance to do more in life and go further, and starting your own side hustle is a great way to do this. You can embark on an exciting adventure and earn more money from it, which will give you more freedom in the future.

Ways that Data-Savvy People Can Make Money with Side Hustles This Year

There are a lot of ways to capitalize off of your knowledge of data science. You can turn these skills into profitable side hustles if you play your cards right.

A side hustle is essentially an activity outside of your normal day job to supplement your income.. This isn’t your full-time job, but something you do, alongside it, to earn some extra money. The whole point of a side hustle is purely to earn some extra money. However, these side hustles often turn into full time and permanent business opportunities.

So now that you know where is a good place to get started and set up with your side hustle. It is time to think about the type of side hustle you want to start up. It’s great to have a platform to help you get started, but you need to know exactly what side hustle that you would like to pursue in the first place.

Here is a list of side hustle ideas for 2022 to help get you started. Remember, anyone can start up a side hustle business, you just have to believe in it to get it running.

Side hustles are an excellent way to earn some extra money and can eventually lead to you having your own business that you work on full time. Below is a list of side hustle ideas to help you get started and hopefully inspire you.

Dropshipping

Dropshipping is one of the most popular and perhaps one of the best side hustles to start in 2022. Dropshipping is a retail business where you can take orders from customers. One of the differences between dropshipping and other retail business ideas is that you don’t keep the goods in stock. Instead, you will work with a company that keeps the stock in their warehouse and the seller accepts the customer orders. When an order comes in, you then communicate with the warehouse where the stock is, to tell them what to send and where to send it to. It’s the perfect side hustle to start, as it’s so easy to do. You don’t have to deal with the hassle of storing the stock yourself and having to send it out, as someone else does this for you. Since it’s so simple, you can start and run your own dropshipping business, you just need to get the basics set up.

You will have a much easier time creating a successful dropshipping business if you are proficient with big data. Here are some reasons that data scientists will have a strong edge over their competitors after starting a dropshipping business:

Data scientists understand how to use predictive analytics technology to forecast trends. This is essential for dropshipping, because you need to know what products to focus on selling.Data scientists know how to leverage AI technology to automate certain tasks. They can use this skill to automate their social media marketing strategy and create new lists more efficiently. Keyword research is an essential part of SEO, which is crucial for any dropshipping business. Data scientists can develop their own customized data mining tools that use the Google Keyword Planner API to find the best keywords for their business.

However, you might still be looking for even easier ways to start a side hustle as a dropshipper. First of all, a great place to get started with your side hustle is with Sellvia. This tools handles a lot of the data analytics and automation features for you.

With the platform Sellvia, it’s great place to start out any type of side hustle business. Sellvia provides support with everything you need to get started. With a side hustle you need to find a supplier, import products to your website and promote your store. These are the basics for starting a side hustle, but all of these things can be done through Sellvia. They provide great support system through the journey too. If you’re thinking of starting up a side hustle in 2022, then Sellvia is a great platform to help you get started.

Create and sell homemade goods on Etsy

If you have a hobby that involves creating homemade goods, then this is an excellent side hustle adventure for you. If it’s something you’re good at doing and enjoy doing anyway, why not sell these creations? Whatever it is you can make, it’s worth trying to sell them and starting a side hustle from your hobby.

You might be wondering how you will have an advantage as a data scientist after starting an Etsy shop. The answer is that Etsy relies on a proprietary search algorithm that was created with machine learning. It uses complex data analytics features. You might have an easier time reverse engineering this algorithm as a data scientist by conducting regression analyses based on observable variables, such as tags, video usage, types of listing images and the presence of certain keywords in listing descriptions. As a data scientist, you can use these insights to better rank your own listings and make a bundle!

Graphic designs that can be printed or used online

If you’re good at graphic designs and know how to use the software to create them, then why not consider selling these graphics? You can either give the option to print and send them or you people can purchase an online copy of the design that they can either use online or print off themselves. If it’s something you already have the knowledge and skills to do, then it’s worth venturing into this as a side hustle. As well as people wanting them for personal use, you will also have businesses that want graphics designing too, so there’s a great variety of potential customers.

We have previously pointed out the benefits of AI and big data for graphic design. You can use data-driven web and graphic design software to assist you.

One of the wonders of AI is that it allows you to automate many design functions through tools like PhotoShop and Illustrator. You can learn more about their batch automation features here.

Blogging

Starting a blog is one of the most popular side hustles that anyone can start. You can write a blog from anywhere in the world and you don’t need a large intial investment to do it either. As long as you have a laptop and internet connection, you can write and upload blog posts wherever you go. They’re also easy to get started with and you can specialize in a variety of things.

If you have a topic, you’re passionate about or have a lot of knowledge in, that’s a great starting point for your blog.  Often, the way to make money from blogs is to include referrals to products or offer sponsors or advertisement on your page.

Blogging is another business idea where data scientists have a huge edge. They know how to use data mining to better identify keyword opportunities. They can also use machine learning technology to create content more efficiently. Furthermore, they can use data analytics more effectively to determine the best performing strategies on social media and create better content.

YouTube

Again, another very popular idea for starting a side hustle, is to start a YouTube channel. This is very similar to a blog, but instead you record videos and upload them to YouTube. These videos could specialize in gaming, be daily vlog of your life or be challenge videos. There is a wide variety of different videos you can record and upload to YouTube. Some people focusing more on lifestyle content and others focus on things like food and gaming. Again, if you have something you’re passionate about, you can use this to create a YouTube channel and share that passion online. You can earn money from this by building up your subscribers, getting paid sponsorships and also form adverts on your videos.

Data scientists also have an edge as Youtubers, because they can can extract the right keywords better with data mining tools. They can also use AI to create better videos for their users. There are even AI video generators on the market, but you can improvise and create a better one as a data scientist.

Become a freelance writer about technology topics

Freelance writing is an excellent side hustle start, as there are plenty of platforms you can get started on. If you’re good at writing, then you’re pretty much good to go. With freelance writing, nothing is really required apart from a laptop to work from and internet connection, so as long as you have these, you can get yourself set up. When it comes to freelance writing, it is often that people will come to you and ask you write an article on a certain topic, which they then pay you for.

You can make a lot of money writing about big data and other technology topics as a freelance writer.

Become a user tester for apps and websites

When it comes to new apps and websites, they all have to be tested beforehand, and people get paid to do this. You can set up your side hustle to be a tester for different types of apps and websites, which you then give feedback on and essentially find any problems with them. This is a great and easy way to earn some extra money.

Sell digital products

Our final idea on our 2022 list of side hustles is to sell digital products. This can be anything from templates, graphics, audio and videos and is basically anything that can be downloaded or streamed. If you can create and sell things like this online, then it’s a great side hustle option. The possibilities are endless when it comes to digital products and what people are wanting, so as long as you can do, you will probably never struggle much for customers.

So as you can see, there is a great variety of side hustle ideas you can start yourself and make some extra money from. At the end of the day, if you have a passion for something or skills and knowledge in a particular area, then this is all you need to help you get started. Of course, there is also the great platform of Sellvia that will help to get your side hustle set up and started.

This is another area where you can stand out as a data scientist. You can create informational products like ebooks and Excel spreadsheets with data that you extracted through data mining tools. You can also utilize AI and data-driven design tools to create better products.

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5 Ways Data Analytics Helps Us Understand the Student Lending Crisis

5 Ways Data Analytics Helps Us Understand the Student Lending Crisis

Data analytics is giving us more insights into many of the most pressing challenges that we have faced as a society. More policymakers are using data to make more informed decisions.

Analytics Insight shared a list of 10 major ways that big data is changing politics. The biggest benefits relate to using big data to understand voters and create models of voting patterns in various districts. However, more politicians are also using data analytics to get deeper insights into some of the biggest concerns facing their constituents.

One of the biggest examples of policymakers using big data is to get a better understanding of the student loan crisis. This is just one of the many applications of data technology in education.

Big Data Helps Understand the Nature of the Student Loan Crisis

Student loans have helped millions of Americans access higher education and kick off their career. So, why are over three-quarters of students anxious about their current finances?

Coupled with higher interest rates and the whopping amount of student debt, the rising cost of education is taking a toll on students’ hopes for their financial futures. But what should today’s borrowers really expect?

Big data is helping us better understand the nature of this fiasco. Sarah Riley, a research economist with the University of North Carolina wrote an paper in 2020 titled Predictive Analytics for Reducing Student Loan Default. As the title suggests, it is geared towards using data analytics to anticipate the risk of a borrower defaulting on their student loans. The goal is for financial institutions to use big data to identify high risk borrowers and avoid giving loans that they will default on.

Riley’s paper addressed the use of applying big data to understand the student loan crisis at the individual level. However, there are ways to use big data to understand it from a microeconomic perspective instead.

Here is what the data is telling us about the growing student loan crisis – and how it can help solve it!

Amounting to $1.58 Trillion Student Loan Was the Second-Largest Debt Component in the US in 2021

At the end of 2021, American consumers reported a cumulative debt of over $15.24 trillion and that figure is growing each year. Most of this is due to mortgages, which account for $10.44 trillion. However, totaling $1.58 trillion, student loans represented the third-largest type of debt in the US, even before credit card and personal loan debts.

At the same time, credit card and student loan debt go hand-in-hand, and those borrowers who are highly educated are also the ones with higher-paying jobs, more expensive lifestyles, and higher credit card debt.

Big data technology is giving us real-time insights about the evolving nature of student loan debt. Policymakers will be able to anticipate future student loan debt levels with predictive analytics tools.

Graduates Walk into The Workplace With an Average Student Debt of $37,113

For many students, the first step into the workplace comes with an already-severe financial burden. Today’s students who have borrowed a federal student loan have an average of $37,113 in debt at graduation, while those who opt for a private lender have an average outstanding balance greater than $40,900.

This is an area where companies using data analytics can benefit as well. They can use data-driven insights to have a better understanding of the situation their customers are facing. Rather than rely solely on the national level student loan averages, they can use data analytics to nuance the data and estimate the data of their own employees based on whether they have a graduate degree, the schools they attended and years they graduated. This will help them come up with the best compensation packages.

Since 1970, Student Debt at Graduation Increased by 2,807%

Student loan debt has been constantly rising since the 70s, skyrocketing by 2,807% over the past 50 years. Even accounting for inflation, student debt has increased by 317% since 1970 and by 157% since the 2008’s Great Recession.

Thanks to the government-supported 0% interest rates introduced as a response to the Covid-19-related financial crisis, the student loan debt dipped slightly at the end of 2021 for the first time since its introduction in 1958.

Bigdata is also helping see how this figure will increase.

In 2021, There Were 44.7 Million Americans With Outstanding Student Loan Balances

Student loans might be the root of most students’ financial worries. However, in 2021, they have helped over 45 million American students access college and higher education. And, nearly 80 million US professionals have accessed a student loan at some point. 

At the same time, nearly 62% of graduates carry student loan debt and over 42 million borrowers still deal with a federal student loan balance.

On Average, Students Take Over 20 Years To Repay Their Loan

Student loans provide value for many years – especially if they allow a student to pursue a high-paying, meaningful career. However, the average borrower can take 20 years to fully repay a graduate student loan. And, for professional graduates who opt to continue their education with a Master’s degree, the repayment period can be as long as 45 years!

While this can be instrumental in helping students access the right job opportunities, it can significantly compromise their ability to regain financial independence over time.

Got Student Debt? Here’s How You Can Pay it Back Faster

Student loans are extremely powerful tools, and, when used correctly, they can help young Americans access high-paying job positions and long-term financial wealth.

Nonetheless, for most households, it can be hard to keep at bay multiple types of debt, including mortgage, credit card balances, and personal loans. That is why your focus should be on paying back your student loan.

Tools such as consolidation loans, refinancing, early repayments, and a professional student loan payoff calculator can help you better understand where you stand and how to pay down debt. Taking advantage of these tools early on is essential to prevent your student loan from becoming unmanageable and continue enjoying benefits from your investment.

Big Data Helps Provide a Better Understanding of the Student Loan Crisis

Big data helps policymakers make better decisions. One of the ways that they are using big data is to get a handle on the student loan crisis. These data-driven insights can help significantly.

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Big Data Offers Tremendous Benefits to Business Intelligence Solutions

Big Data Offers Tremendous Benefits to Business Intelligence Solutions

Business intelligence can help you gain a more accurate perspective on how your business is performing using key performance metrics. By 2023, 33% of companies will practice decision intelligence.

Are you looking to use business intelligence to optimize business and security operations? Read on for an explanation and analysis of how business intelligence can leverage data to guide optimizing business and security operations.

What Is Business Intelligence?

Business intelligence refers to the acquisition, processing, and presentation of actionable data to provide a clearer picture of your company’s performance. Business intelligence requires in-depth data leveraging and analysis using key performance metrics (KPIs). 

There are many benefits of using data in this capacity. This is one of the reasons that the demand for data scientists is exploding and more people are pursuing this career path. Since data is constantly moving during business intelligence operations, additional security measures need to be implemented to ensure no weak spots at different points during data processing.

Why Should You Use Business Intelligence?

Business intelligence has many advantages and will help provide a fuller perspective on data for the basis of your business intelligence. Some of the main benefits to adopting business intelligence include:

Protecting data – cybersecurity breaches can cause significant financial damage, and data needs to be covered in each stage during processing. One of the reasons business intelligence can help is due to better encryption standards. Protecting clients – 2FA and access control can help you protect both the company’s interests and the clients.Lowering risk – to avoid litigation, your company needs to ensure compliance to prevent the risk of causing security breaches.Mitigating concerns – business intelligence can help you mitigate concerns and earn the trust of your clients.

How BI Can Help To Optimize Business And Security Operations By Leveraging Building Data

Here are some business intelligence strategies that can be implemented to leverage data and improve business and security operations.

Using Access Control Technology

You can use access control technology to aggregate and visualize data leveraged for business intelligence. By installing access control technology, you will be able to use building security solutions to enforce internal and external access restrictions in your office buildings. Not only will this protect the physical assets in your business and sensitive client information, but it will also protect any servers within the building, acting as both a physical and digital security measure. 

You can use business intelligence to leverage the data gained from an access control system to provide access intelligence. Access intelligence can provide you with analysis features using access rights and reports activities, such as:

Ready-to-use and preconfigured reports that you can distribute via email notification.Self-serve business intelligence reports that can help to provide individual reports based on specific information needs.

Workspace And Space Management Optimization

you can use data gained from access reports to implement workspace and space management optimization. By installing internal access control that restricts and grants access to individual spaces within buildings, you can view data on space utilization. 

This data will then provide you with the necessary information to determine a need to downsize your office space or expand office space to accommodate business operations.

A Converged Physical And Digital Security Strategy

you can use access intelligence data in a converged physical and digital security strategy to provide a fuller picture of security needs. By combining physical and digital security teams in your business infrastructure, you will increase communication and efficiency in leveraging security data. 

Since the internet of things (IoT) and cloud-based technologies are blurring the lines between physical and digital assets, there is an increased need to use physical and digital security information in conjunction with one another to increase business intelligence and provide a more futureproof security strategy.

Authenticating Permissions and Access To Restricted Areas

Access intelligence data is a powerful tool in your overall business intelligence. Access to this information should thus be restricted to a limited number of company leaders with the clearance to handle such sensitive information. 

If an unauthorized user accesses this information, it can have severe consequences. It is not necessary to share this information with employees or stakeholders, even if you feel it is safe. Ensure that you only provide this business intelligence module to those who need to access it in supervisory or management contexts.

Ensuring The Best Cloud-Based Options

Since the pandemic, cloud-based technologies have become a staple feature in business operations to allow remote access to essential data. However, safeguarding the data stored on these cloud-based technologies has thus become a significant concern. Internal audits are necessary to determine whether your current security measures are sufficient or whether an additional layer of security is needed.

Summary

Business intelligence can help you to leverage data from different sources, including physical and digital security information; you can use that to optimize your business operations. You can leverage physical and digital security data to ensure protection for cloud-based options, optimize your workspace, and create a more futureproof security strategy. Business intelligence can help you maximize security and encourage more trust from stakeholders and clients.

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Choosing Between Outsourced Vs In-House Data Management Strategies

Choosing Between Outsourced Vs In-House Data Management Strategies

There is no question that data has become a valuable asset to almost every organization. Companies use big data to optimize their marketing strategies, maintain better relationships with their customers, manage their financial strategies and improve human resources capabilities.

Unfortunately, data isn’t always easy to manage. You need to rely on the services of a well trained specialist that understands the nuances of big data technology. This explains the growing opportunities for people looking for careers as a data scientists.

It is Important to Find the Right Approach to Manage Your Data Effectively

Data is the backbone of almost every business, yet it can be difficult to know how to manage it. While most businesses start out with one or two IT professionals, your requirements can quickly outpace what they are able to provide. Moreover, IT is a broad church, and the staff you have in-house may not be able to expand into the services you want or need. They may not have experience as data scientists, so you might need to hire a professional to assist you.

Conducting work in-house is often seen to be better than outsourcing by default, but this isn’t necessarily true of IT. While outsourcing your data management strategy isn’t always the best solution, it does confer a number of unique advantages – and can be both cheaper and more flexible for businesses on certain scales.

What is the difference between an in-house and outsourced data management strategy?

In-house IT is where you employ a dedicated staff member or team to manage your IT infrastructure. They will be on site to perform maintenance, upgrades and installations, and provide technical support where needed. They will become the face of IT in your organization, extracting all the benefits of IT while smoothing over any problems. They might also be able to help manage your data, but that is going to depend on their training and proficiency with data management. Data science is a very specialized skill that not all IT professionals can handle.

Outsourced IT is where all or part of your IT department is outsourced to an IT managed services company. The external company will use the collective expertise and manpower of its staff to provide the same services as an in-house team, as well as its hardware and infrastructure to provide a range of services, such as cloud hosting and data storage.

Advantages of in-house IT

In-house IT can be both a starting point and endpoint for many businesses. It’s not unusual for businesses to employ an IT specialist or two in their formative stages to implement and oversee key services and establish a strong digital framework, which will be crucial for any data-driven organization. Used on a small scale, it may be that having one person oversee your IT infrastructure is more cost-effective and practical than employing an external service provider for relatively small tasks.

Conversely, many larger businesses will have a substantial in-house IT department to keep their gargantuan infrastructure running smoothly. As well as providing on-site and remote technical support, they will oversee things like data rooms and data centers and give the business a large degree of control and autonomy when developing and implementing new digital products or services.

In-house IT works well when your needs are limited or hyper-specific. Having an in-house IT team allows for IT to be embedded within your business in a way that both gives you absolute control over your IT, and develops a mutual understanding of IT. Your IT department will have a stronger understanding of your culture and needs, and the rest of your business will benefit from the exposure to and interactions with your IT department. They will also have full autonomy over your data, so you don’t have to worry about a third-party data management service leaking it.

Disadvantages of in-house IT

The area where in-house IT providers encounter problems is when you need to scale your data capacity. As you require more and more varied IT services, you will likely need to store more data and hire more IT staff with different specialties. This presents not just a financial issue, but one of managing your IT department, and having the knowledge to make good hiring decisions. Without knowing exactly what you need from your IT, your IT department could become bloated, and your services ineffective. This is especially true if you have sophisticated data needs.

You’ll also face limits on what you can do with your IT services, and how quickly you can react to problems. While an in-house IT team is beneficial when reacting to issues during working hours, you won’t have anyone to help if a website or service goes down outside of office hours, or if your site or servers get hacked. You may also not have the manpower to undertake certain projects, either slowing you down or forcing you to hire employees you may only need temporarily.

Advantages of outsourced IT

The greatest advantage of an outsourced IT service provider is its flexibility. With the ability to scale up or down as your business’ needs and requirements change and your data needs evolve, outsourced IT makes it much easier to pivot to new services, and test out new ideas. If you have a temporary project to undertake, you’ll immediately have access to the manpower you need, without having to hire more workers.

Outsourced IT also tends to be more cost-effective than in-house IT, especially if you manage a much larger volume of data. The relative benefits you’ll get from harnessing multiple IT experts will be far cheaper than hiring those experts yourself, and you’ll only be paying for them when you need them. Instead of paying flat salaries, you’ll be able to adjust what you pay depending on what you’re using, scaling your involvement with the IT service provider up or down as required.

Perhaps most crucially, you’ll have support that you can rely on whenever you need it. Outsourced IT service providers are generally on-hand 24/7, ensuring that you have reliable technical support at all hours. This is not only great for supporting international businesses operating in different time zones, but also for monitoring your internal data and reacting to issues, minimizing data center and website server downtime and responding to data security breaches.

Disadvantages of outsourced IT

While an outsourced IT service provider will strive to forge a close connection with your business, they are only as accessible as you allow them to be, and you may find it quicker or easier to communicate with an in-house IT team. This is particularly true if you have complex requirements that you find hard to communicate, or which are particular to your company’s culture or industry niche.

Working with an outsourced IT service provider also requires a high level of trust. As mentioned, IT is of critical importance to many businesses, because it is a major driver and facilitator of sales. To make the most of your IT strategy, you’ll need to maintain strong links with your IT service provider and ensure that they gain a full picture of your requirements, both in the present and the future.

Of course, there is also the option of trying to have both! It’s not uncommon for some businesses to have both a substantial in-house IT department and utilize an IT service provider for some outsourcing. This may be sensible if your business has specific IT requirements that are best served by in-house IT professionals, such as a very specific piece of industry-related software, but also has needs such as cloud hosting outside of their remit.

Whether you choose to use an in-house or outsourced IT (or both!) will depend on the role IT plays in your business, the amount of data you will store and how this role is likely to expand in the future. While in-house IT has its place – particularly in larger organizations – outsourcing your data management strategy is likely to give you the flexibility and cost-savings you need to scale more effectively and reinvest in improving your digital infrastructure.

Sota is one of the UK’s leading independent providers of professional IT services in Kent, cloud computing, cyber resilience, connectivity, and unified communications. Having worked with countless businesses over the years, they are experts in their field, ready to advise and offer tailored solutions for each and every company.

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5 Reasons No-Code Platforms Are the Future of Data Science and AI

5 Reasons No-Code Platforms Are the Future of Data Science and AI

Data science is an evolving profession. Artificial intelligence is also changing at a remarkable pace. A number of new platforms and tools are being regularly rolled out to help data scientists do their jobs more effectively and easily.

Savvy data scientists and AI developers are keeping up with trends and learning the new technology that can help them work more efficiently. One of the biggest trends is the introduction of low code and no-code data platforms.

No-Code Platforms Are the Future of Data Science and AI

There is a significant shift in tools, processes, and skills being used in the enterprise. As a result, low-code/no-code next-gen technologies are starting to reach the enterprise. As enterprises increasingly look to outsource or bring in third-party providers, they are starting to embrace low-code/no-code tools.

There are a lot of great reasons to embrace no-code platforms. One of them is the fact that they make AI technology more available to businesses. This is a topic that Harvard Business Review author Jonathon Reilly discussed in an article back in November.

No-code platforms are also becoming more valuable for data scientists. One example is with Obviously AI. This is a company that boasts its commitment to providing data science solutions to companies without the need to create code. Dubbed a “No Code Startup for Data Scientists”, Obviously AI received $4.7 million in seed funding last summer, according to a report by TechCrunch. This underscores the tremendous demand for a codeless approach to data science.

In some cases, the new tools are replacing the on-premise enterprise solutions that have been custom-developed in the past, which creates valuable new features for data scientists. In other cases, especially where a third-party solution is brought into an organization on a more temporary basis, low-code/no-code platforms provide the perfect alternative to outsourcing.

These low-code/no-code tools can be used by experienced application experts as well as subject matter experts who have little to no programming knowledge, which makes them very popular with enterprises because no-code tools speed up development time and cost savings without the need for hiring expensive developer resources. Although most data scientists have at least moderate programming capabilities, most of them are not hardcore experts in the various languages they might need to be proficient in to develop applications from scratch. They also have better things to do than spend hours debugging code.

Here are five reasons why data scientists in many enterprises are turning to low-code/no-code platforms.

1. Overwhelmed development teams and talent shortage

At the most basic level, IT teams are becoming increasingly overwhelmed with so many applications, digital journeys, and tools being developed. Data scientists are no exception.

In many cases, there is a significant time lag between a request and when that request is fulfilled. This takes up a lot of the team’s time and creates frustration among various stakeholders. Given the growing number of data requests that organizations face, data scientists can’t contribute to this bottleneck.

In addition, having to hire expensive resources means that organizations are paying out significant sums for very niche skill sets. Not only does this contribute to the high cost of developing data science projects, but also directly impacts budget and timelines. Low-code/no-code tools have a much lower barrier to entry and expertise required, so can be used by experts as well as those with limited experience.

2. Demand for new apps is increasing exponentially

As more and more applications come online, demand for new applications is quickly outstripping the ability of development teams to produce them. A recent McKinsey report found that 40% of application development projects fail to meet the intended business goals.

The research also shows that  Over 60% of the Enterprise Software projects are delivered late—with 16% being double the amount of time anticipated or more! Data scientists can help streamline their delivery by using the right platforms.

3. Enterprises recognize third-party solutions as a viable development platform

Enterprises are starting to recognize that giving non-technical employees no-code tools to accomplish certain tasks and processes reduces costs and also contributes to increased agility. Given the evolving nature and growing complexity of data science projects, this makes no-code tools a huge selling point.

This is especially true for many of the application development initiatives that enterprises embark upon each year, which require either small scale projects or outside expertise.

Delegating these tasks to citizen developments can be very cost effective and provide quick access to specific skill sets or domain knowledge.

4. Need for speed

Everyone wants to be “agile” these days, but the truth is that most organizations still tend to move at a rather sluggish pace compared with the rate of technology change. Even data scientists struggle to handle these projects efficiently.

Enterprises understand that their advantage in the market can be eroded quickly if they don’t embrace new technologies and innovate at a faster rate. They want their data scientists to have the best technology at their fingertips.

Low-code/no code platforms provide a quick route to market for new ideas or concepts, as well as the ability to build out proof-of-concept apps that can be used internally as demos before going through a full development cycle. Enterprise-grade no-code platforms also integrate well with existing enterprise technologies, including CRM systems.

5. Need for cost savings

Every IT department faces the same problem of diminishing budgets and increasing pressures to prove ROI for every initiative. Low-code/no code platforms are often relatively inexpensive, which means they are very affordable even if only used on a temporary basis to build out proof of concepts.

These platforms also have a low learning curve, so can be picked up by subject-matter experts with little or no formal development training. This reduces the need for expensive developer resources and speeds up development time.

In conclusion, enterprises are increasingly turning to low-code/no code platforms as an agile method of developing new applications that let them turn new ideas into working solutions, and then scale up to the production environment when ready.

The market for these platforms is growing quickly and there are lots of good options available at different price points.

One area of enterprise digital transformation that can be solved with no-code is customer data collection, such as forms and paperwork in insurance and banking.  With EasySend’s no-code platform you can build forms that are integrated into your CRM and internal systems without having to wait months on the IT department, while ensuring that your customers get great digital experience at every step.

Codeless Platforms Are the Future of Data Science

More data scientists are relying on platforms that don’t require coding. This saves them time and helps process tasks much more efficiently.

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Big Data is an Important Part of Library Marketing Strategies

Big Data is an Important Part of Library Marketing Strategies

We are all in awe of the changes that big data has created for almost every industry. The implications of big data is more obvious in some industries than others. For example, we can all appreciate the tremendous changes that data science has created for the financial industry, healthcare and web design.

The impact developments in data technology have had on other industries have gotten far less publicity, but that doesn’t mean it hasn’t been significant. Academic and public libraries are among those heavily influenced by these changes. Ninety-three percent of public libraries have digital collections. Big data is helping them increase the number of digital resources they offer.

In 2019, Science Publishing Group shared a study on the impact of big data on academic libraries. The study underscored the benefits of using it for customer data storage, media usage and indexing. However, there are a lot of other benefits of using data technology when managing a library.

One of the overlooked benefits of big data for libraries pertains to marketing. Libraries are less popular these days, because people can get so many resources online. Therefore, libraries have to actively market their services to reach new patrons. Big data can help them with this.

Big Data is the Key to a Successful Library Marketing Strategy

Library professionals in both academic libraries and public libraries should be trained marketers and for a good reason. Untrained library staff can really have the toughest time of their working history when it comes to library management. 

Such hurdles can become problems, especially when the untrained marketers are trying to find ways to promote your library services and related marketing activities. The same librarians may face challenges when promoting library programs and making marketing plans beyond the usual printing of fliers.

This is where data-driven marketing strategies become so important. Library marketers can use big data to better identify their target demographic, personalize their recommended books for new customers and reach customers more cost-effectively.

Marketing concepts and trends rapidly evolving, as big data plays a more important role. So, some inexperienced marketers may not keep up with these changes that library users need, especially if they aren’t very data savvy. This is where data-driven marketing strategists can be invaluable for library services. They can provide helpful tips, and library resources needed to help them get started.

These tips are based on key library marketing strategies such as search engine optimization and social media management and strategic planning among others. Read on to find out effective marketing skills and information resources every librarian needs to stay in the game.

1. Use Data Analytics to Craft the Perfect Social Media Management Strategy

At the moment, using social media to manage and promote library services may seem to be a little intimidating. This is always the case if you are an upcoming marketer, or your library has a brand new social media account. You also have to worry about wasting a lot of time creating content that simply won’t resonate with your intended visitors.

Managing more than one social media account can easily be overwhelming to untrained library promoters. This is simply because you have to constantly work to create a great social media strategy that goes beyond just posting and engaging with your target audience.

Data analytics has made it a lot easier to manage your social media marketing strategies. You will be able to leverage analytics technology to see what strategies are performing the best. On top of that, a social strategy that relies on using a service such as Sprout Social can enable you to make posts and view each social media account from one platform. Most importantly, Sprout Social will play a critical role in the tracking of your analytics so you may decide what is working and not working for you.

2. Use Data-Driven CRMs to Create a Stellar Email Marketing Strategy

An email marketing strategy is a quick and effective way to reach out to many patrons directly. Strategic approaches to marketing library services works well when your target patrons are not in the library.

With an email marketing strategy, you can start collecting all important contact information with the help of sign-up sheets. You may carry out this task right in the library, information centers, or at conferences. Once you have obtained the right information, you may proceed to create an up-to-date newsletter sign-up box and upload it to your library’s website homepage.

A lot of customer relationship management (CRM) tools are great for handling these tasks. They use large data repositories to keep track of all of your customer details, which makes tracking customers much easier.

To come up with specific lists of contact information, you may require services like MailChimp and Constant Contact. These vital marketing tools will use databases to enable you to organize contact names of patrons such as legislators, local teachers, job seekers, and others in specific demographics. Whenever you want to share this information, you can just blast all personalized emails to your lists at the press of a button.

3. Create a Data-Driven Search Engine Optimization Strategy

For most librarians, search engine optimization (SEO) may sound like a strange tool for marketing of library and information services. However, SEO as it is commonly referred to, is one of the search engine marketing strategies that you should encourage your employees at the library to apply in their market research strategy.

Big data is helping improve SEO strategies. SEO strategists use big data to uncover link building opportunities by data mining backlinks to competitors, discover overlooked keyword opportunities and assess the likely performance of different webpage formats.

On the flip side, you may not realize the importance of SEO in social networking if you are running a small library within a close-knit community. Regardless of this downside, you can still use SEO to help you steer your target audiences to your library’s website if you use the right data-driven SEO strategy. Turn to Google Analytics and Moz to help you identify or track your webpage traffic, resolve web problems like broken links and improve your website presence.

4. Adopt a Digital Signage Strategy

You can as well make your marketing strategies for libraries effective by the use of digital signage. The digital signage can display information about your library events, opening and closing hours, and show the content of your library in the form of PowerPoint files, Word, or PDF on crystal clear screens.

Digital signage can help you advertise special offers at your library at the press of a button. They can as well play a crucial role during new librarian and patron orientation. Most importantly, signage can strengthen library security even at university libraries. All you have to do is to incorporate your newly acquired digital signage screens into your library security strategy and everything else will fall in place much to your delight.

Key benefits of adopting a digital signage strategy include the following:

Increase in patron motivation with rewards and gamificationImpressing library users with compelling photos and video contentShowcasing library facilities for user satisfactionMaintaining secure and central control of available content while depending on remote updatingReference services and management

Big Data is a Big Deal for Library Marketing

There are many things data professionals can learn from librarians. However, librarians also benefit form data.

In fact, libraries are more dependent on big data than ever before. In addition to using big data to store resources, they are also using it to improve their marketing strategies. Many marketing strategies for libraries are available today. All these strategies can help you reach out to as many patrons as possible in addition to enhancing librarianship. Choose the most appropriate strategies, implement them with data technology, and use them to promote your library services to a wider audience.

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Data Analytics and Social Media: Twin Pillars in the Evolution of Business

Data Analytics and Social Media: Twin Pillars in the Evolution of Business

META: We’re breaking down the ways social media has changed businesses and how you can use these changes to get ahead.

Digital technology is unquestionably changing the future of business. Two of the biggest advances in technology that are influencing the direction of business are social media and data analytics. These may seem like unrelated technologies to the average person, but they are actually closely intertwined.

Smart businesses will need to know how to leverage data analytics to make the most of their social media strategies. They will get more bang for their buck if they take a data-driven approach to social networking.

Data Analytics and Social Media Are Collectively Shaping the Future of Business

There isn’t a lot that the internet cannot influence in some way or another. The idea of going “off grid” is almost laughable when you think about it. A big part of being on the internet has to do with social media. Once upon a time, we only spoke to long-distance family members or friends we’d just seen in class on social media. Those days are long over. Today, we are treating our Instagram accounts like resumes and making business connections on Facebook and selling everything on Instagram.

Big data is another area that is changing the nature of business. One study from 2020 discovered that 59% of global companies use data analytics to some degree.

Data analytics and social media can go nicely hand-in-hand. In fact, there is an entire field known as social media analytics, which is described in this post on IBM. How do these two technologies overlap? According to IBM, here are some benefits of using the two together:

Companies can use social media analytics to identify industry trends to update their own offerings and respond to customer expectations.Businesses using social media analytics are able to better understand the messages of their customers and better assess how their own messages are interpreted.Social media analytics makes it easier to identify the best value of features of various products.Social media analytics is arguably the best competitiveness analytics tool available. Companies can use social media analytics to better understand the impact third-party companies and partners may have on performance.

In this post, we will break down the ways social media has changed businesses and how you can use these changes to get ahead.

Social Media Analytics Helps Make the Most of Virtual Events

Networking used to be a simple concept. You would go where people congregated and start introducing yourself. The core concept hasn’t changed that much, but as businesses are integrating all around the world, the increasing move onto the internet, and travel bans being implemented, it makes sense that there is a growing demand for virtual industry events.

These virtual events are not as pointless as you might think. You can listen to (or give) a talk, chat in groups, or ask for an aside with someone in particular. The events themselves are full of activities for you to take part in, like interactive games and “speed networking”, which is exactly how it sounds.

Social media analytics makes it easier to get the most of your networking opportunities. You can use extract social data to see how many people usually participate in various events. You can also data mine testimonials about various meetings, so you can derive better insights about the benefits people have gotten from them. You can use MeetUp Pro’s analytics tools if you host your own business Meetup events. Other analytics tools like Hootsuite, BrandWatch and Buffer are also great.

If you like the idea of hosting a virtual networking opportunity and you’re in the UK, contact RX for a consultation to find out how you can better promote your business.

Remember when the rule on social media was, don’t put anything too edgy on there in case an employer sees it? Well, some crazy kids are taking that a step further and are creating and honing their social media accounts around the idea of impressing an employer.

When you think about it, it’s not such a crazy idea. It’s an open secret that employers are checking social media accounts to be sure they’re hiring a fine, upstanding citizen, and if you have a hobby, you’re considering trying to make some money from, like art or music, the first move you make is to create a dedicated social media account.

Get the Most from Your Social Media Profiles

So, it only makes sense that people are displaying the fruits of their individual labors on social media for employers to browse. Everything from academic milestones to personal projects are being displayed, with the added bonus of demonstrating your skills in the process.

Plus, hosting an impressive social media account takes a lot of transferable skills, like photo and video editing, organizational skills, marketing skills, and if you’re making money from it, business and entrepreneurial skills.

However, you might want to know whether or not your profile is actually helping. The good news is that analytics tools like Google Analytics can help make this determination. You will be able to integrate Google Analytics with most social media profiles, including Facebook profiles and LinkedIn ads. You can also use SalesForce with most social media profiles, which gives you access to their analytics dashboards.

Social Media Analytics Helps Us Identify Changing Behaviors

Social media is a very different place from what it once was and users’ habits have drastically changed over the past couple of years. For one thing, users are researching any brands they buy from today, to make sure their priorities align with their own. There are a lot of social issues you can tap into to get on their good side with this, like supporting small businesses, sustainable products, or charities.

Plus, users are becoming more aware of adverts and demand quality content, causing marketers to shift focus from outlining the benefits of their product, to incorporating their product into otherwise entertaining marketing.

Social media analytics helps make it easier to track these changes. As a company, you can use specialized social media analytics tools and standard analytics tools like Google Analytics to make the most of your strategy.

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5 Types of Business Technology Every Entrepreneur Should be Using

5 Types of Business Technology Every Entrepreneur Should be Using

Running a small business can be difficult; you have to do multiple things simultaneously – and sometimes it’s not enough. However, technology proves to be handy when it comes to streamlining things and helping you save money and time.

In fact, most successful companies depend on technology for almost every aspect of their businesses. And while there are many types of technology available, choosing to go digital does not have to be a headache.

The following are some common types of business technologies you should know:

Productivity software and tools

Every successful organization excels on a simplified workflow to meet vital timelines. Productivity tools like Microsoft Calendar and Google sheets can be of great help. Google sheets is an online collaborative spreadsheet used by business owners to organize sales, financial plans, customer lists, and other business data with their team.

Google Hangouts is an excellent productivity tool that can help you start a video call or even text your colleagues at any time. This will, in turn, save you money and time in gathering everyone in one place.

Customer Relationship Management System (CRMS)

Part of a business’s successful business strategy is understanding consumers’ behaviors and using the data collected. This is where a customer relationships management system comes in.

Typically, CRM enhances your business performance by boosting up-sell and cross-sell chances. Cross-selling is when a customer is offered a free product almost similar to the product they buy.

On the other hand, up-selling is when you offer a customer a premium product related to those they buy. CRM allows you to perform these strategies with ease. You will know what your customers want and their pattern of purchase. Your sales team can then use this information to identify the appropriate time to promote specific products.

Financial accounting system

Like manual bookkeeping, a financial accounting system allows business owners to manage their revenues and expenditures online. This said, the right system will depend on the needs and size of your business.

QuickBooks will be the best if you are running a small business as it is easy to set up and retain. On the other hand, accounting systems like Sage Accpac and SAP Business One will be best for you if you are running a big business. This software provides you with more integrations and customization with other systems.

Inventory control system

Modern entrepreneurs use the inventory control system to handle all inventory. This system tracks product supplies digitally. For example, the system automatically updates every time new inventory arrives or whenever a product is sold. So, by having such a system in place, your company can keep correct records when managing inventory and have the right amount of supplies in your store, depending on your company’s financial plan and sales prediction.

Social media scheduling tools

Small business owners know the significance of social media to connect with their potential clients. However, being on social media can be time-consuming. Most people go to their social media apps, only to snap out of it some minutes later. The good news is that social media scheduling tools allow you to schedule when you want your posts to go out public without getting into the social media accounts. The best part is that you can write your content early and start your promotion when you want to grow your business without spending a lot of time on social media.

Bottom line

There are many choices regarding technology, tools, and platforms that can help you grow your business. Once you have identified what you want to accomplish, set aside some time and research the suitable option for your business. Some of these tools can even eliminate the need for additional employees and keep your overhead cost down.

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Serverless Kubernetes Has Become Invaluable to Data Scientists

Serverless Kubernetes Has Become Invaluable to Data Scientists

Data science is a growing profession. While it involves more opportunities than ever, it also has a lot more complications. Standards and expectations are rapidly changing, especially in regards to the types of technology used to create data science projects.

Most data scientists are using some form of DevOps interface these days. One of the most popular is Kubernetes. Kyle Gallatin recently recorded a Kubernetes tutorial that was presented at the New York City Data Science Academy, which illustrates the importance of this platform for his profession.

There are a lot of important nuances for data scientists using Kubernetes. One of the most important is the adaption of serverless Kubernetes.

In this post, we will look at how serverless is changing the traditional Kubernetes architecture. However, we will first address the benefits of Kubernetes in data science.

Benefits of Kubernetes for Data Science

Kubernetes is based on a control node combined with multiple worker nodes to facilitate its cluster architecture. Workloads then get distributed to these worker nodes while being managed by the control node. With the emergence of serverless technologies, there is growing interest in utilizing serverless within Kubernetes both to manage workloads and provide the cluster itself.

It should be relatively obvious why data scientists can benefit from this interface. Bob Laurent, Senior Director of Domino Data Labs has talked about some of the biggest reasons. He points out that Kubernetes allows scalable access to GPUs and CPUs and helps with infrastructure abstraction. These features make data science projects scalable, cost-effective and easier to manage.

Why Serverless in Kubernetes?

Kubernetes is clearly a useful feature for data scientists. After this is understood, it is important to come to terms with the wonders of using it in a serverless enviornment.

First of all, it is important to dispel a misconception. Serverless does not mean the absence of servers. It just means that the server is abstracted to a certain level that users do not need to consider how their applications are executed. You only have to simply provide your packaged application or a container, and the serverless platform will manage all the underlying infrastructure considerations. This means it can still be used to handle data projects at different levels of your infrastructure.

Even with all the advantages Kubernetes brings, users still need to manage the underlying servers. While managed K8s reduce this burden somewhat, it still does not eliminate servers completely from the equation. They will manage the control plane, yet you still have to provision and manage worker nodes on the various data science projects you are working on.

Serverless implementation like AWS Fargate completely eliminates the need for data scientists to manage the worker nodes and moves the workloads into serverless architecture. This approach completely shifts the responsibility of server (node) management from the user to the service providers. Serverless can also bring cost reductions, as users only pay for the resources used. Furthermore, it ensures no overprovisioning has occurred while having the flexibility to scale as needed.

Kubernetes without Nodes?

Each worker node has an agent called kubelet that connects it to the Kubernetes API. When a user interacts with the Kubernetes API via kubectl commands, kubelet allows each node to receive instruction from the API on how to manage the pods in the specific nodes. Kubectl also uses PodSpecs to manage the underlying pods whenever a kubelet is running on a server and connected to K8s API.

This opens a lot of doors for data scientists trying to boost scalability and customize their projects. The biggest benefit in data science projects boils down to virtualization.

In a serverless setting, this functionality is typically emulated by a virtual kubelet. This allows the Kubernetes API to recognize the virtual kubelet implementation as a node within a cluster. However, this virtual kubelet will schedule containers elsewhere, typically in supported backends like AWS Fargate, AWS Batch, HasiCorp Normad, etc… Although users can interact with the K8s cluster usual way the underlying containers will be scheduled in serverless containers services. Thus, with this implementation, users can gain the advantages of serverless without sacrificing the functionality of Kubernetes. The best part of a virtual kubelet is it even allows for mixed configurations, where actual worker nodes and virtual kubectl can coexist within a cluster.

Deploying Serverless Workloads in Kubernetes

In a non-serverless setting, the users would create the container and then configure K8s manifests and resources to deploy and run the application within the cluster. Additionally, we have to configure the scaling and preconfigure the resource utilization. For a serverless implementation, there can be two approaches to do it called container as a Service (CaaS) and a Function as a Service (FaaS)

Container as a Service (CaaS)

With CaaS, we provide the container with the necessary configurations, and CaaS will create and manage all the underlying secondary resources, including Istio routing, scaling, ingress, etc… CaaS will then configure the container and manage it depending on the configurations provided. The only requirement is that the container is able to interpret the commands sent by the CaaS service and act upon them, which will require some additional configurations or libraries in the container itself. A good example of CaaS would be Knative to deploy serverless workloads in Kubernetes.

Function as a Service (FaaS)

FaaS takes CaaS implementation a step further. In CaaS, the user needs to provide the container in a FaaS service. The user will create and upload a function with a source code and additional configurations’ information like runtime, triggers, etc… However, FaaS will build our code and containerized the application with all the necessary management tools and libraries and deploy them, simplifying the application deployment. OpenWhisk, Kubeless, OpenFaaS are some FaaS services available to facilitate this functionality.

In both these instances, the functionality of these services will be built on top of the Kubernetes API, exposing only the CaaS or FaaS interface to the users. All the deployments and management will be carried out using the Kubernetes API. But users would only see the much simpler function or container service interface. Combining this with a completely serverless cluster powered by a virtual kubelet, you can have a complete serverless Kubernetes environment.

Kubernetes is a Wonderful Resource for Data Scientists

There are many powerful new platforms that data scientists should be willing to take advantage of. By integrating Kubernetes with serverless platforms and services, data scientists can gain the benefits of both of them without compromising their functionality. At a cluster level, serverless helps reduce costs while providing near-unlimited scalability and availability without management responsibilities. At the application level, serverless greatly simplifies the development and deployment effort required to deploy and use containers in a Kubernetes environment, either via CaaS or FaaS implementations.

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Best AI Twitter Automation Tools Marketers Should Use in 2022

Best AI Twitter Automation Tools Marketers Should Use in 2022

AI technology is changing many aspects of modern business. More companies are using AI technology to automate their social media marketing strategies.

We previously mentioned the benefits of using data analytics to make the most of social media marketing. However, AI is arguably even more important.

Social media is a highly profitable way to market. With Twitter being one of the most popular sites today, it’s imperative to be a part of it. Opportunity awaits! But first, you have to know the latest tools of the trade so you can get the most out of your endeavor.

These tools use complex AI technology to make it easier to automate your Twitter marketing strategy. This will help you boost the ROI of your digital marketing efforts.

​Twitter’s Hottest AI-Driven Bots and Tools for 2022

If you want to maximize your marketing efforts on Twitter, automation is definitely the way to go. This wouldn’t be possible without sophisticated advances in AI technology. You can stay a step ahead of the competition by gaining notice instead of falling under the radar. With so many users, it’s easy to get lost in the shuffle, so ensure that you don’t by implementing AI-driven marketing tools that will boost your popularity.

Automation will help you engage and expand your audience. You will be able to comment, follow, schedule, campaign, increase traffic, learn behaviors, tweet, and retweet — almost any manual Twitter task can be done automatically! Isn’t it time you worked smarter and not harder? AI technology has come a long way, so you might as well make the most of it.

Let these third-party tools help you get the job done with ease.

​Seek Socially

This is an automation solution for those who don’t want to be bothered by the tedious ins and outs of Twitter engagement yet still desire a high following. At Seek Socially, they’ll do your growing for you by leveraging the power of artificial intelligence! Initially, you fill out a survey that details your expectations, and then they’ll take care of the rest. As a fully managed service, they’ll cut hours away from your daily tasks and interactions. It’s a solid tool for serious users.

​Tweet Attacks Pro

This is AI-driven account management like you’ve never seen before. It is especially useful if you’re employed by an agency that holds multiple accounts, this is the smart-task resource you need for organization. Designed for those with a huge presence, it’s a streamlined and integrated experience like nothing else. None of this would have been possible without a savvy team of AI developers behind the company.

​FollowingLike

FollowingLike is a great AI automation tool for any serious and dedicated Twitter user. It’s considered an expensive product for those who desire a short-term application. However, for long-term implementation, it’s extremely cost-effective. Featuring clear-cut modules for easy viewing and control, this incredibly flexible AIO bot was made for organized management.

​SidesMedia

One of the most trusted social media marketing services out there, SidesMedia is a staple for many Twitter users. It’s customer-friendly and readily available to answer your questions. With decent pricing and quick performance, you can’t go wrong with this tool. Plus, it’s also great for other sites, such as Instagram and even Pinterest. Just be sure to safeguard yourself. Click here for more information on how to optimize your security, as it should be your top priority.

​Twesocial

Twesocial’s model is all about naturally growing your audience. It focuses on gaining real followers while avoiding surfacing on Twitter’s radar. Offering a number of targeting and simplification features, it’s a fantastic tool for those who don’t have a lot of time to spend on social media yet require a large marketable audience.

​Tweriod

This one’s all about analytics. However, what sets Tweriod apart is that it places a heavy focus on your competition as well as potential followers. If you’re not a fan of procrastination and prefer a high amount of information, Tweriod is probably the best tool for planning ahead, organization, and knowledge.

​Media Mister

Media mister has been developing ever since social media’s public inception into daily life. Therefore, its legacy cannot be disputed. It’s arguably the most refined bot on the market today. It’s also ideal for many other sites, but its reputation for impeccable Twitter automation is unparalleled.

​Tweeteev

Not exceptionally prevalent in the world of social media automation, Tweeteev is one of its best-kept secrets. It’s a simple, user-friendly growth service that gets to know you first. Believing that ideal followers are actually people who will appreciate your marketing, Tweetev takes the time to learn who you are in order to find an audience that’s specific to what you’re offering.

​Audiense

A diverse operation, Audiense covers a wingspan of users. If you’re new to the game, it’s a wonderful way to get started. Simple to navigate, it’ll have you up and running in no time! Once you progress to an experienced level, you can take advantage of its detailed features, like message campaigns and influencer targeting.

AI Technology Makes Twitter Marketing Easier than Ever

These are just some of the automated tools on the market today. They have all been made possible with sophisticated advances in AI technology. As we have said before, AI is the most disruptive change in marketing.

All highlight both shared and unique features that cater to specific needs. Take the time to find what’s best for you, and make sure you’re smart about it. Protect your investment with Twitter proxies, so you don’t risk security threats. Stay safe when you’re marketing online!

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