Here’s what you missed at Next ’21

Here’s what you missed at Next ’21

Google Cloud Next ‘21 is over, but the learning is just beginning. With three days of keynotes, deep dives, and announcements, there was a lot to take in! But don’t worry if you missed something—the Google Cloud Blog team is here to round up our favorite announcements of Next ‘21.

The biggest announcements

You can catch up on all the Next announcements in this comprehensive list, but we know that’s a lot! Here are the standouts.

Living on the edge

You get a cloud … and you get a cloud! We think Oprah would approve of Google Distributed Cloud, announced during Monday’s Thomas Kurian keynote: a portfolio of fully managed hardware and software solutions that extend Google Cloud’s infrastructure and services to data centers and the edge.  Distributed Cloud is powered by Anthos, which also got a slate of upgrades this week including VM support, and you’ll find it useful in all sorts of situations from running low-latency edge workloads or private 5G/LTE solutions to meeting local sovereignty requirements. Reality at the edge is messy, but managing it doesn’t have to be.

Google security on your side

The Google Cybersecurity Action Team (GCAT) might sound like a cult-classic 80s Saturday morning cartoon lineup, but it’s also a group of security experts we’ve assembled to bring Google-grade security chops to governments and businesses around the world. You can rely on them for threat briefings, proven security blueprints, and strategic sessions designed to help you build a trusted cloud. To get things started, GCAT has released a Security and Resilience Framework using Google Cloud and partner technologies. Now we just need to work on a theme song.

AI breakthroughs for industry

Buzzwords begone. The whole point of machine learning and AI is to do something with it, something that helps your business. So we’ve made Contact Center AI (CCAI) Insights generally available, and also added Contract DocAI to our DocAI lineup. CCAI Insights helps you mine contact center interactions to create better customer experiences—whether your call center is staffed by humans or virtual agents. Contract DocAI makes it faster and less expensive to analyze contracts, the most critical documents of all. Both are business tools that solve real problems—no buzzwords necessary.

Sprucing up with the cleanest cloud

Google Cloud is proud of our sustainability track record as the cleanest cloud in the industry. But we want to help you go even further. With the newly-announced Carbon Footprint tool, every Google Cloud user—that means you!—can access the gross carbon emissions associated with the services you use in Google Cloud. Now you can measure, track, and report your carbon footprint. Plus we’ve integrated sustainability into Unattended Project Recommender, so you can reduce your footprint even further by deleting unattended projects.

Data analytics unite!

Unification was the theme of this year’s data announcements. Vertex AI Workbench launched in public preview—a single Jupyter-based environment for data scientists to complete all of their ML work, from experimentation, to deployment, to managing and monitoring models. But it’s not just for Vertex AI—you can also analyze data from BigQuery, Dataproc, Spark, and Looker in one interface.

And don’t sleep on the private alpha launch of BigQuery Omni, which takes that theme of unification even further by allowing you to analyze data from other clouds using BigQuery. Later this month, you’ll be able to securely query S3 data in AWS or Azure Blob Storage data in Azure directly through the familiar BigQuery user interface, bringing the power of BigQuery to where the data resides. 

Collaboration gets cloudier

Google Workspace (the artist formerly known as G Suite) is a core part of Google Cloud, and we announced all sorts of exciting updates and integrations to our collaboration products this year. Client-side encryption for Google Meet, Data Loss Prevention (DLP) for Chat, and Drive labels for sensitive files are all new at Next. Perhaps most critical for organizations is our just-announced Work Safer Program, which helps protect your Google Workspace users against rising cybersecurity threats with industry-leading solutions from Google and our partners.

Keeping the band together

Throughout Next, we were proud to celebrate our most innovative customers, partners, and community members. And we want to keep the good vibes going all year long with our new Innovators community. You’ll get the inside scoop on our roadmap, get access to exclusive events, and much more. Everyone is welcome to join, and we’ll have all sorts of cool opportunities for Innovators coming up. Join the program today to stay informed and come along on the journey. 

Keynotes and sessions

The live sessions are over, but you can still register to view sessions on demand through November 5th. We’ve created a collection of themed playlists to guide you—whether you’re a developer, an executive, or an industry expert, you’ll find something helpful here. If you’ve got time for just one session, we recommend CEO Thomas Kurian’s keynote, which covers many of this year’s biggest announcements.

Thanks again for learning and growing with us in 2021. We’ll have more Next recaps and breakdowns coming up on the blog in the weeks to come—stay tuned!

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Spark on Google Cloud: Serverless Spark jobs made seamless for all data users

Spark on Google Cloud: Serverless Spark jobs made seamless for all data users

Apache Spark has become a popular platform as it can serve all of data engineering, data exploration, and machine learning use cases. However, Spark still requires the on-premises way of managing clusters and tuning infrastructure for each job. Also, end to end use cases require Spark to be used along with technologies like TensorFlow, and programming languages like SQL and Python. Today, these operate in silos, with Spark on unstructured data lakes, SQL on data warehouses, and TensorFlow in completely separate machine learning platforms. This increases costs, reduces agility, and makes governance extremely hard; prohibiting enterprises from making insights available to the right users at the right time.

Announcing Spark on Google Cloud, now serverless and integrated

We are excited to announce Spark on Google Cloud, bringing industry’s first autoscaling serverless Spark, seamlessly integrated with the best of Google Cloud and open source tools, so you can effortlessly power ETL, data science, and data analytics use cases at scale. Google Cloud has been running large scale business critical Spark workloads for enterprise customers for 6+ years, using open source Spark in Dataproc. Today, we are furthering our commitment by enabling customers to:

Eliminate time spent managing Spark clusters: With serverless Spark, users submit their Spark jobs, and let them do auto-provision, and autoscale to finish.

Enable data users of all levels: Connect, analyze, and execute Spark jobs from the interface of users’ choice including BigQuery, Vertex AI or Dataplex, in 2 clicks, without any custom integrations.

Retain flexibility of consumption: No one size fits all. Use Spark as serverless, deploy on Google Kubernetes Engine (GKE), or on compute clusters based on the requirements.

With Spark on Google Cloud, we are providing a way for customers to use Spark in a cloud native manner (serverless), and seamlessly with tools used by data engineers, data analysts, and data scientists for their use cases. These tools will help customers on their way to realize the data platform redesign they have embarked on.

“Deutsche Bank is using Spark for a variety of different use cases. Migrating to GCP and adopting Serverless Spark for Dataproc allows us to optimize our resource utilization and reduce manual effort so our engineering teams can focus on delivering data products for our business instead of managing infrastructure. At the same time we can retain the existing code base and knowhow of our engineers, thus boosting adoption and making the migration a seamless experience.”—Balaji Maragalla, Director Big Data Platform, Deutsche Bank

“We see serverless Spark playing a central role in our data strategy. Serverless Spark will provide an efficient, seamless solution for teams that aren’t familiar with big data technology or don’t need to bother with idiosyncrasies of Spark to solve their own processing needs. We’re excited about the serverless aspect of the offering, as well as the seamless integration with BigQuery, Vertex AI, Dataplex and other data services.” —Saral Jain, Director of Engineering, Infrastructure and Data, Snap Inc.

Dataproc Serverless for Spark

Per IDC, developers spend 40% time writing code, and 60% of the time tuning infrastructure and managing clusters. Furthermore, not all Spark developers are infrastructure experts, resulting in higher costs and productivity impact. With serverless Spark, developers can spend all their time on the code and logic. They do not need to manage clusters or tune infrastructure. They submit Spark jobs from their interface of choice, and processing is auto-scaled to match the needs of the job. Furthermore, while Spark users today pay for the time the infrastructure is running, with serverless Spark they only pay for the job duration.

Spark through BigQuery

BigQuery, the leading data warehouse, now provides a unified interface for data analysts to write SQL or PySpark. The code is executed using serverless Spark seamlessly, without the need for infrastructure provisioning. BigQuery has been the pioneer for serverless data warehousing, and now supports serverless Spark for Spark-based analytics.

Spark through Vertex AI

Data scientists no longer need to go through custom integrations to use Spark with their notebooks. Through Vertex AI Workbench, they can connect to Spark with a single click, and do interactive development. With Vertex AI, Spark can easily be used together with other ML frameworks like TensorFlow, Pytorch, Sci-kit learn, and BigQuery ML. All the Google Cloud security, compliance, and IAM are automatically applied across Vertex AI and Spark. Once you are ready to deploy the ML models, the notebook can be executed as a Spark job in Dataproc, and scheduled as part of Vertex AI Pipelines.

Spark through Dataplex

Dataplex is an intelligent data fabric that enables organizations to centrally manage, monitor, and govern their data across data lakes, data warehouses, and data marts with consistent controls, providing access to trusted data and powering analytics at scale. Now, you can use Spark on distributed data natively through Dataplex. Dataplex provides a collaborative analytics interface, with 1-click access to SparkSQL, Notebooks, or PySpark, and the ability to save, share, search notebooks and scripts alongside data.

Flexibility of consumption

We understand one size does not fit all. Spark is available for consumption in 3 different ways based on your specific needs. For customers standardizing on Kubernetes for infrastructure management, run Spark on Google Kubernetes Engine (GKE) to improve resource utilization and simplify infrastructure management. For customers looking for Hadoop style infrastructure management, run Spark on Google Compute Engine (GCE). For customers, who’re looking for no-ops Spark deployment, use serverless Spark! 

ESG Senior Analyst Mike Leone commented, “Google Cloud is making Spark easier to use and more accessible to a wide range of users through a single, integrated platform. The ability to run Spark in a serverless manner, and through BigQuery and Vertex AI will create significant productivity improvement for customers. Further, Google’s focus on security and governance makes this Spark portfolio useful to all enterprises as they continue migrating to the Cloud.”

Getting started

Dataproc Serverless for Spark will be Generally Available within a few weeks. BigQuery and Dataplex integration is in Private Preview. Vertex AI workbench is available in Public Preview, you can get started here. For all capabilities, you can request for Preview access through this form.

You can work with Google Cloud partners to get started as well.

“We are excited to partner with Google Cloud as we look to provide our joint customers with the latest innovations on Spark. We see Spark being used for a variety of analytics and ML use cases. Google is taking Spark a step further by making it serverless, and available through BigQuery, Vertex AI and Dataplex for a wide spectrum of users.” —Sharad Kumar, Cloud First data and AI Lead at Accenture

For more information, visit our website or the watch announcement video and our conversation with Snap at Next 2021.

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Data-Driven Pitch Deck Examples for Inspiring the Next Big Screenwriter

Data-Driven Pitch Deck Examples for Inspiring the Next Big Screenwriter

Big data has been very important in the creative and entertainment sectors. Many artists are using big data to improve the quality of their work. Screenwriters are no exception.

We mentioned in the past that big data has been very valuable for Hollywood. Professionals throughout the industry are looking for ways to integrate big data into their jobs.

A growing number of screenwriters are discovering the wonders of big data. Fast Company wrote about this back in 2013 when they said that Big Data is Rewriting Hollywood Scripts.

“Improved data collection and management through surveys, feedback, HR databases, and bias-interrupter and bias-decoder tools are essential in gaining nuanced inclusion insights and thus fostering organization-wide DE&I when insights are fed back into the organization in an actionable way,” writes Fast Company author Mark Wilson.

Screenwriters can’t bring to life their scripts on-screen without producers. In a world where it’s hard to find directors, producers, and workforce to create a film, screenwriters need something ample to sell their concept. This can be where big data comes in.

There are no shortcuts to selling your pilot script, as well as pitching a TV show during in-person meetings. You need to step up your presentation by using these investor pitch deck examples! This is the most powerful tool you can use to convince producers to invest in your pilot episode. Tools like this use complex data-driven algorithms to come up with the best deck examples for aspiring screenwriters.

If you can write your ideas and script on a piece of paper, then you can use big data and AI technology to create visuals for the presentation. What you need is a solid case to support your vision, and you can put it together with the help of a presentation deck. You can also use data analytics and AI to assess how various pitch decks are likely to find those that are likely to perform the best.

Let’s assume it’s your first time building a pitch deck from online software, and you’re not sure what design to incorporate in your presentation. But don’t sweat it. We can help you get that collaboration you want from prospective producers, directors, and actors in no time. All you have to do is continue reading! 

How Do You Make a Pitch Deck with Data Analytics Tools?

Without a doubt, you already know what your project or TV show is going to be about. However, you are torn between multiple data-driven software applications on the internet available for building a killer deck. For a fully interactive tool, Venngage is an excellent place to start. 

In our online deck maker, certain factors need to go into your deck. You should make sure that you include these factors in every slide chronologically. If you reconsider, it may be a lose-lose situation for you and your audience. Data analytics tools can make this a lot easier, but you have to deploy them correctly. They will help understand the timeframe of various situations and make sure they are arranged in chronological order.

A successful pitch deck should leave your potential producers and directors feeling like they know what exactly your TV show will feel like. And it’s your job to pull off a convincing presentation. Though we will leave the task of editing to you, taking a look at these tv show pitch deck examples will help you achieve a good collaboration.

Let’s dive into the film pitch deck examples that were developed with big data technology and specifics of what your TV show should look like. 

Title Page


First of all, an appealing pitch deck needs a killer opening page. Undoubtedly, this is the first thing your audience will see, which could compel them to keep listening to your idea. Your title page should include a resemblance of the screenplay and the name of your TV show. And since the text and image are the only things of substance on the first slide, picking the right font and picture is hugely significant.

You can use data-driven design tools that leverage AI technology to help create your opening page. This will help make sure that it makes the best possible impression.

Like the example above, the pitch deck title page only includes a few texts and a compelling image.

The Screenplay

Once you get past the title page, the next task is to summarize the elements included in the screenplay. Of course, you already know what these would be: treatment, character breakdown, pilot script, logline, and show bible. 

While you cannot show all the details and nuances of your script in these slides, you should offer your audiences a clean overview of the film. However, you must keep in mind not to include too much text. They might get lost in a wall of words or dialogue. The best way to keep the following pages engaging is to keep them short and precise. In other words, brief and impactful synopsis and theme decks. 

Here are more ideas for what your screenplay deck should look like. 


As you can see in the example template above, the pitch deck also shows consistency with its theme and text throughout the entire presentation. When using data analytics tools to pick a theme for the slides, ask yourself a few questions: What is your TV show trying to say? What is the mood or tone of the series?

If you’ve found the questions to your answers, find a template from the website that matches your TV show’s mood. From there, you can communicate your style and vision for your series in an impactful manner.


For the last few pages of your deck, let your audience know who will be on board for this project. Take note: these pages should not be very long. Include a general overview of the crew. You can also write a brief blurb about your co-scriptwriters and other people who already signed up for this project.

Below are the examples you can utilize when presenting your team:


The people to whom you are pitching your TV show do not only have to like your concept — they have to like you, too. So let them know you have come prepared and are great to work with by showing them a professionally made TV show pitch deck.

It’s always about how you sell your remarkable project to them. Work with every resource available on the website to make the next big TV show happen. There is a large database that can help you find what you are looking for.

Big Data is Ideal for Creating the Best Pitch Decks for Screenwriters

Netflix isn’t the only entertainment company to use big data. Many screenwriters are using big data as well. There are a lot of great pitch decks that you can use to be a more successful screenwriter. You need to know how to utilize big data technology to leverage them properly.

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5 Tips to Stay Competitive as AI Technology Evolves

5 Tips to Stay Competitive as AI Technology Evolves

The market for AI technology is growing remarkably. Businesses around the world spent over $60 billion on artificial intelligence last year alone and the demand is expected to continue to rise.

Businesses spend a lot of time and resources on marketing to stand out from their competition. While marketing remains relevant and essential, AI technology provides endless opportunities that create a massive edge between you and your competitors. AI technology helps businesses respond to change and new business opportunities effectively.

Artificial intelligence technology also boosts supply chain efficiency and improves communication between teams for the fast delivery of strategic projects. As technology improves, the need for businesses to compete increases. Here’s how to stay competitive as technology evolves.

1. Leverage innovation

AI technology moves innovation forward by boosting tinkering and experimentation, accelerating the innovation process. It also allows companies to experiment with new concepts and ideas in different ways without relying only on lab tests. Technological advancements enhance human capabilities by helping you overcome cognitive shortcomings, pushing you towards a great innovative capacity. Choose the right artificial intelligence tools such as System Innovation to help you manage innovation and confront the challenges of technological advancements. Aligning your innovations with changing consumer behavior gives you a competitive edge in the relevant industry.

2. Automate processes

One of the biggest benefits of AI is that it has led to new breakthroughs in automation. Automating processes can be costly, but it’s a worthy long-term investment that helps businesses align their strategies for streamlined operations.

When you automate repetitive tasks with AI technology, your operations become quick and more seamless, saving time and improving efficiency. This leaves employees more time to focus on process improvement and product development, placing you ahead of the competition. Process automation eliminates the need for paper and physical storage space, cutting costs and allowing you to redirect the savings towards strategic technology investments that help you stay competitive.

3. Take advantage of data analytics

The evolution of technology has seen the amount created each day increase drastically. One of the biggest reasons AI has become so valuable is that it is so tightly integrated with data analytics. Using data analytics technology, you can study this data to gain valuable insights to help with decision-making. This allows your business to remain competitive as data-driven decision-making is more accurate and precise. Data analytics enables you to observe consumer patterns to acquire and retain customers by understanding their behavior and delivering what they want. Observing customer trends helps you create targeted campaigns that meet or surpass client expectations, building brand loyalty.

Big data also helps you identify potential business risks and offers effective risk management solutions. Using data insights, organizations can track customer feedback, determine product success, and what their competitors are doing, helping them stay competitive as they no longer rely on instincts.

4. Consider improving user experience

User experience plays a crucial role in determining how customers interact with your product or service. One of the best benefits of AI is that it can help improve the user experience through features like personalization. Your product or service design and user experience are significant considerations for competitive advantage. Thanks to technological evolution, you can take advantage of online tools to track customer behavior to understand their preferences and create an offering that matches those needs, giving you a sustainable competitive edge.

5. Use machine learning

Machine learning is one of the biggest applications of AI. It allows you to access and analyze extensive data quicker than humans to get insights that you can apply to your business strategies to beat the competition. It also helps you look at customer data relating to their patterns, trends, and preferences to better understand your clients and adjust your strategies to create marketing campaigns they resonate with, meet their needs, and more.


Competitive advantage not only gives you an edge over your competitors, but also boosts business growth. Consider using the above tips to help you stay competitive.

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What is the Best AI-Driven App for Video Conferencing?

What is the Best AI-Driven App for Video Conferencing?

Artificial intelligence is helping facilitate many aspects of business. Many companies have been forced to lean more heavily on AI technology than ever during the pandemic, because they had to find new ways to encourage social distancing.

Even as the pandemic starts to wind down, many companies are still relying more heavily on AI technology to adapt to a new age that is dependent on digital strategies. In fact, we talked about the benefits of this software a few years before the pandemic and it has clearly become even more popular since.

One of the most promising applications of AI technology is the utilization of new video conferencing technology. But what app is the best for these purposes?

Leveraging AI Video Conferencing Apps to Improve Communication

It’s no doubt that all video conferencing apps have more or less similar functions with a little difference. While most of them are relying on AI to provide the features that they need. Some programs are suitable for one-on-one conversations; some are perfect for chats in small groups; while others are capable of handling large webinars and masterclasses involving hundreds of people. 

Back in January, Adilin Beatrice wrote an article about the use of artificial intelligence in video conferencing apps. There is no denying the fact that AI has been invaluable.

But is there an ideal app that can arrange various kinds of virtual events regardless of the number of participants? Luckily, yes. Meet CallOut – the service that boasts all the features a modern video calls software is required to have by using sophisticated AI technology.

Their team of experienced developers selected the most useful AI tools for arranging video conferences, upgraded them, and created something unique. Let’s examine the best features CallOut offers its customers:

1. Outstanding connection quality

When you want to hold a video call, its quality is highly important. Their team has already taken care of that by using AI to improve the development process.

CallOut offers Full-HD video and audio for each user. Forget about times, when the connection was lost or you see just a pixelated version of a person on the other side of the screen. 

Additionally, we put the sound under full control:

Speech separation by audio splittingMuted background noise

It really is a great example of the benefits of AI-driven video conferencing software.

2. Unique AI and ML-based software

Let a bit of artificial intelligence into your everyday life:

Gesture recognition

Make use of your body language turning gestures into emojis, changing presentation slides with a single handwave!

Beautification tools

Videoconferencing with AI takes virtual meetings to a whole new level. It allows fixing camera drawbacks, reaching the ideal balance between the natural look and retouching, and letting you keep rocking a work-from-home aesthetic.

Virtual 3D backgrounds

Breathe life into plain white walls, designing your own stylish virtual space. Say no to meeting rescheduling because your home is a mess. In a couple of taps, you can replace any background with a preferred one!

Cloud recording

Save missed business meetings, conferences, and webinars to the cloud storage for future playback. The smart technology assesses the displayed emotions and prepares short footage of every call. Don’t have time to watch it? Just read the transcript of the most relevant information.

3. 100% secured chats

One of the biggest advantages of using a video conferencing tool that is developed with AI is that it has much more robust security. There are no more leakages of personal data! The service uses the latest web protection to ensure the total encryption of everything said and shared at any online gathering. No one will ever get access to your personal data, even the CallOut team. 

Moreover, we offer some extra security tools, such as:

Private in-meeting chatCustom personal meeting IDHost controls (lock meeting, mute all, and participant control)

4. User-friendly interface

Their service is developed based on customers’ needs. 89% of the clients say an ideal application for online video conferencing should be quick and easy to use. AI has been very helpful in improving usability.

That’s why it takes a minute to start a conversation in CallOut.

Forget about the long registration process, just open the link a meeting host shared with you and you’re in a virtual room keeping in touch with your colleagues, family, and friends.

5. Compatible with all modern devices

Use their service on any of your devices – PC, laptop, tablet, or smartphone. 

You can install the application from the market, or just open your favorite browser, go to the official website and start chatting with anyone you want, any time it’s required.

Make the right choice!

Whether you’re a part of a large corporation with hundreds of employees, a small startup with a huge desire to succeed, or just an individual looking for an online video calls service, be sure – CallOut is built to satisfy your needs.

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6 Data-Driven Tips to Dramatically Improve User Experience on Your Site

6 Data-Driven Tips to Dramatically Improve User Experience on Your Site

We have talked about the benefits of using big data in web design. One of the most important benefits of data analytics is improving user experience.

Jenny Booth highlighted this in her post Data-informed design: Getting started with UX analytics. We wanted to cover this topic in more depth.

Big Data is Crucial for Improving Online User Experience

Companies that use data technology strategically are able to significantly boost their overall conversion rates. One of the most important reasons is that they can use data from their users to see how they respond to various webpage elements. This allows them to take a data-driven web optimization approach for better user engagement.

Users are the lifeblood of any website. The more the end-users enjoy your site, the more likely they will return and recommend it to others. If you want to keep your leads coming back again and again, you need to make sure that each visit is as engaging as possible. This is where data-driven customer engagement strategies comes into play.

Your website might be the most aesthetically arranged piece of code on the block, but that won’t mean much if it isn’t well-designed. Good web design means that every element of your web presence—from content strategy and usability testing to design conception and development—should consider target demographic and user experience. You need to take all of this into consideration when using big data in your web design approach.

Implementing even one of these methods can lead to fundamental changes in how customers interact with your brand. Here are six tips for designing a web presence that does more than just load code. 

Consult a conversion optimization agency with a focus on data analytics

If you’re not already working with an agency that has experience optimizing the customer journey for conversions, then now is a great time to explore hiring one. You need to make sure that this company has a background in data analytics and knows how to use it in their design process.

By taking advantage of relevant big data tools and methods during the design process, you can ensure you’re directing users down an efficient path toward conversion without wasting their time clicking in circles around your site. In addition, using a conversion optimization agency like Ampry can help provide insight into how users use your site, arming you with valuable data for any future development projects. 

Conduct A/B testing

Another way to increase conversions is with A/B testing. This is one of the biggest benefits of data analytics. This website design and optimization method involves running two different versions of the same page against each other and then measuring which one converts more users into leads or sales.

While you’ll need to hire a web development company for this one, it does show just how vital user experience can be. If you don’t get it right on the front end, then there’s no point in worrying about how well your site converts visitors when they arrive at the home page.

Leverage persuasive storytelling

The most effective marketing campaigns tell a story, and this rule applies to websites as well. These stories don’t necessarily have fictional villains and plots with characters like novels or films, but rather real-life narratives about people who have benefitted from using a particular product or service. A narrative engages users and draws them in while also allowing you to demonstrate your value proposition.

You can use data analytics for this process as well. There are a lot of online advertising spy tools that allow you to mine data from other advertisers to see what types of storytelling approaches work for them, so you can replicate them yourself.

Make it personal, make it human

Creating a website that feels like it’s part of a larger community can also boost conversions. This personalization is something that isn’t easy for every company. Still, if you have the resources to implement this approach onto your site, then you’ll be rewarded with increased engagement among users and repeat visits.

Just remember to keep the human element front and center at all times. Suppose visitors feel like they are speaking directly with an actual person rather than just another money-hungry business entity. In that case, consumers are more likely to form emotional connections with your brand and align with your values.

Simplify forms and pages

Forms and landing pages are some of the most critical components of user experience on any website. That’s why it’s essential to keep these pages as simple as possible to encourage users to move through the conversion funnel more quickly.

Using minimal entry fields is one way to do this, but another is by personalizing these requests with information users have already provided through social media integrations. This is one of the areas where AI tools can help with the design process. You can even use AI and data design technology to make sure the forms are sized according to the user device and integrate other personalization factors.

Focusing on the user journey

Despite what some might say, a website is not all about the home page. Your homepage is just one small piece of the puzzle that unfolds as users move throughout your site–think of your homepage as the welcome mat and foyer of your business’s home. First impressions are essential, but that doesn’t mean you should put the cart before the horse when designing your page.

Suppose you’re able to map out exactly how each page contributes to or affects other parts of this journey. In that case, you’ll better understand your users and their needs, which means more opportunities for conversion optimization and higher conversions overall. 

This is the biggest benefit of data analytics. You can use tools like Google Analytics to map their journey and optimize accordingly.

Data Technology is Invaluable for UX Optimization

Consumers are spoiled for choice in today’s e-commerce market, but that doesn’t mean you can’t be a cut above the rest. By integrating data-driven design principles and prioritizing user experience, you can convert your leads into sales with the best of them.

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Be the Best – 9 Ways to Market Your Business with Big Data

Be the Best – 9 Ways to Market Your Business with Big Data

Big data technology has been a highly valuable asset for many companies around the world. Countless companies are utilizing big data to improve many aspects of their business. Some of the best applications of data analytics and AI technology has been in the field of marketing.

Data-Driven Marketing is More Important than Ever

The competition out there is fierce, so it is vital that you find ways to make your business stand out from the crowd. Your approach to marketing your company should be unique and exciting to snare customers. Your product and service should be top class to retain them. This is where data-driven marketing strategies come into play.

If you are looking to increase your customer base, here are 9 ways to successfully market your business by leveraging big data tools.

Exercise Search Engine Optimization

Big data has become essential for modern SEO. We talked about the applications of using big data in SEO in the past. However, before you can create a data-driven SEO strategy, you should understand the benefits of SEO in the first place.

When you have a fantastic website, you want to make sure that as many customers as possible enter it. You have to be near the top of the list on a search engine page like Google to glean the maximum customer traffic.

When building and adding information to a website, you must think about search engine optimization and use keywords and phrases that customers are likely to type into a search engine. This is one of the ways that big data can be most helpful. You can use sophisticated data mining tools to get the keywords you need to create a successful campaign. When a specific word or group of words is entered into a search engine the same way it appears on your website, the viewer will be presented with your website as one of the top clickable options. Log file analysis and natural variations of that help company website builders better understand how search engines are working on their websites and gather ideas on ways to improve their SEO performance.

Create a Quality Website

Big data has also been very important in developing websites. You can read our previous article on using big data for website development.

Online shopping has been more popular than ever since the unwelcome appearance of COVID 19 across the world, forcing society into periods of home quarantine. People have turned to the internet to buy goods and hunt for service providers, so it is crucial that you have a website for your business.

A top-notch website is one that is easy to navigate, interesting, informative, and easy on the eye. If your website is crammed with unnecessary literature and it is confusing or awkward to locate specific information, the potential customer will rapidly lose heart and turn to another website. You can use data-driven analytics tools like Crazy Egg to help optimize the site.

Use clear photographs depicting every angle of your product. List the dimensions, colors available, and any other relevant details, but keep the description short. Ensure it is easy for the client to check out items in their cart and offer various payment options. Publish precise contact details of your company so that customers can contact you quickly should they have any issues.

Boost Sales with a Brand and Logo

Some of the world’s most successful companies have a logo and branding that is instantly recognizable such as McDonald’s Golden Arches or the half-eaten fruit of Apple. Often people will remember a symbol but not a name, so it makes sense to develop a visual identity for your company that customers will instantly think of when they are looking for a particular product or service.

This is an overlooked area where big data can be highly useful. You can use data-driven design platforms like Canva to create great website content.

Be a Social Butterfly

These days it is imperative you have a social media presence as around 70% of US inhabitants have a social media account, whether it be with platforms such as Facebook, LinkedIn, or Instagram. You can’t afford to be an effective social media marketer without using big data these days.

On sites such as Facebook, you can advertise, open a store, and communicate with customers all over the world for free. Your Facebook site can display photos of your products and links to your website or YouTube channel – another essential accessory for a successful business. A YouTube channel devoted to your company allows you to be creative with your advertising while reaching out to customers in all corners of the world.

You will need to use data analytics tools like Google Analytics or Hootsuite to optimize, automate and improve your social media strategy.

Develop an App

Rather than scouring through web pages, many people like to use an app on their phone or tablet. Big data is also proving to be useful for app development.

Create an app for your customers that is simple and speedy to use, and you will find that they keep coming back for more. Apps help customers feel more engaged with your company and make your business more visible.

Write a Blog

Including a blog on your website can help you attract traffic. A well-constructed and entertaining blog can engage people and make them want to come back to read subsequent blogs. Some fans of your writing may share the blog on their social media pages or email links to friends and family. Get blogging as it may just expand your customer base.

Ask Affiliates For Assistance

Bloggers and YouTube influencers can do wonders for the sale of your product.

Look on social media platforms such as YouTube for people who use products similar to those you produce and ask them if they will include your wares in one of their videos. For example, suppose you manufacture paints and art supplies. In that case, you could ask a popular artistic YouTuber such as Moriah Elizabeth to use and promote your products on some of her videos. Followers of the influencer will be keen to buy the products their idol uses, and the influencer will be content as they will receive a percentage commission from sales made through the link to your products on their site.

Many of the top influencers have hundreds of thousands of fans from nations across the globe. Brands used on YouTube videos by these people have been known to sell out in minutes.

You can use big data to help with your affiliate marketing strategy as well. You will be able to monitor the ROI of different affiliate traffic sources and rule out affiliate fraudsters if you use analytics properly.

Be Seen Everywhere

You need to be seen in order to be successful, so get your company out there. Invest a decent amount of money on advertising in local and national newspapers, billboards, radio, and television.

Initially, it may seem like you are emptying your wallet, but widespread quality advertising will do wonders for your sales. Consult a professional marketing company about how to advertise your product best, visually, verbally, and aurally. They can help you compose a catchy jingle for your radio and television advertisements or an eye-catching full-page spread for the local rag.

Make Useful Merchandise and Be Generous with Freebies

Everyone loves a freebie, so devote some of your budget to creating innovative merchandise or handing out free samples of your products.

If your business sells food or drink products, you could set up a stall at the local market and hand out free samples of the goods. Once people taste your cuisine, they will be desperate to buy more.

Pass out merchandise such as pens or clothing around local businesses or at business expos. Wear branded clothes yourself when you are out and about or have business livery printed onto your vehicle.

There are thousands of ways you can promote your business – just make sure your method grabs the public’s attention. Above all, ensure your goods or services live up to the hype!

Big Data is Vital to Modern Marketing

You can’t overlook the importance of big data in the marketing field. Make sure that you use it wisely, so you can get the most bang for your buck.

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Why Investing in Data Is Crucial for Business Growth In 2022

Why Investing in Data Is Crucial for Business Growth In 2022

There’s no denying that data is everywhere in life. The rate at which information is being collected is growing exponentially, with approximately 2.5 quintillion bytes (that’s 2,5000, 000, 000, 000, 000, 000!) of data being produced every day.

As technology continues to advance data generation across the world, it’s safe to say that investing in data solutions will be crucial to seeing business growth and success in 2022 and beyond.

How can data help my business?

There are many ways you can use data to your business’s advantage. Ultimately, data helps firms understand and improve their processes, reducing money and time spent on wasted resources. It has been very useful in countless industries, including financial trading.

IBM estimates that 90% of all data generated by the Internet of Things (IOT) is not analyzed, or utilized in business decision processes. Despite this, there are four key areaswhere data can help to shape better understanding of how your business is running – and plenty of tools to help you get there!

Understanding performance

As a starting point, there are a number of tools that utilize data visualization for businesses. It’s important to regularly implement performance mapping, to ensure your company is continually making improvements to be the best it can.

Sometimes, it can be hard to spot aspects of a business that aren’t running as smoothly as they could be. For this reason, exploring data visualization can come in handy. From

Google Charts to Tableau, there are so many tools and analytics software options available for your business to thrive.

Understanding employees

Business owners can leverage data to understand their workforce better. By gaining deeper insights into the needs of your employees, you can help to provide a better overall experience and workplace environment.

Surveys and email communications can be used to gain insight into employee satisfaction levels. By asking for feedback, employers will gain greater respect from their staff, who will feel as though their voices are being heard.

Often, smaller companies don’t have structured Human Resource (HR) processes in place, and cross-department communications are under strain. Cross-sharing of data can aid this, with platforms like ScreenCloud helping to ensure teams are being heard.

Understanding customers

Providing a good customer experience is becoming more and more important. Consumer expectations are rising, and without tracking behaviors at various points in the customer journey, you won’t be able to make improvements to the experience you’re providing. There are so many ways that online data can be leveraged through analytics and software to improve your offering.

Data is important in all aspects of online marketing and advertising, helping businesses find new potential customers, improve conversions and ensure loyal customers are being nurtured. The bottom line is, in a world that now values speed, ease and efficiency, if you don’t ensure you’re providing these factors, it’s likely you’ll find customer retention difficult.

By better understanding your customers better, you will be able to leverage your data and boost company sales moving forward.

Understanding competitors

Competitor analysis is crucial to understanding your market share position. In order to gain a competitive advantage, you need to fully understand what you’re up against. Data can be used to show your competitors’ strengths and weaknesses, helping you to realize how your own business strategy can be enhanced for optimal performance.

Investing in data solutions

If investing in data solutions hasn’t been a top priority for your business so far, now is the time to make it one! In order to remain ahead of the game, data solutions should be integrated to your business processes to ensure optimum performance.

When thinking about your budget for the next quarter, it’s a good idea to leave some money aside for data. Alternatively, you could consider low cost unsecured funding as a short-term solution that will have long term results. Though data can be expensive, it offers one of the greatest return on investment (ROI) for businesses.

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Biggest Trends in Data Visualization Taking Shape in 2022

Biggest Trends in Data Visualization Taking Shape in 2022

There are countless examples of big data transforming many different industries. It can be used for something as visual as reducing traffic jams, to personalizing products and services, to improving the experience in multiplayer video games.

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. This is something that you can learn more about in just about any technology blog. We would like to talk about data visualization and its role in the big data movement.

Data is useless without the opportunity to visualize what we are looking for. As we have already said, the challenge for companies is to extract value from data, and to do so it is necessary to have the best visualization tools. Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields). However, there will always be a decisive human factor, at least for a few decades yet.

What is data virtualization?

Data visualization is going to grow in importance in the short term. Data visualization is a concept that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that may go unnoticed in text-based data can be more easily exposed and recognized with data visualization software.

Data virtualization is becoming more popular due to its huge benefits. Companies are expected to spend nearly $4.9 billion on data virtualization services by 2026.

This is of great importance to remove the barrier between the stored data and the use of the data by every employee in a company. If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future.

There is little use for data analytics without the right visualization tool. What benefits does it bring to businesses?

In the era of Big Data, the Web, the Cloud and the huge explosion in data volume and diversity, companies cannot afford to store and replicate all the information they need for their business.

Data Virtualization is a technology that allows combining information from different data sources and transforming them into a single virtual data source that can be accessed in real time by different applications.

In this way, it is possible to exploit the business value of all data, of any type and from any source. It also generates integrated and standardized data services that help you get more agile performance from your data without the need for constant replication.

Why is Data Virtualization the cheapest and fastest option?

Physically moving and storing the same data in different repositories multiplies costs and slows down processes when IT changes need to be made. Data Virtualization allows accessing them from a single point, replicating them only when strictly necessary.

In which projects or use cases is Data Virtualization ideal?

Data virtualization is ideal in any situation where the is necessary:

Information coming from diverse data sources.Real-time information.Agile requirements and fast deployment times.Multi-channel publishing of data services.

Agile BI and Reporting, Single Customer View, Data Services, Web and Cloud Computing Integration are scenarios where Data Virtualization offers feasible and more efficient alternatives to traditional solutions.

Does Data Virtualization support web data integration?

The web is inherently large, dynamic, heterogeneous, and the fastest growing source of information. Data Virtualization can include web process automation tools and semantic tools that help easily and reliably extract information from the web, and combine it with corporate information, to produce immediate results.

How does Data Virtualization manage data quality requirements?

Data Virtualization includes capabilities for integrating, transforming and enriching information, based on rules and extensible with specific third-party products. It can control changes in the sources from which it extracts data and includes Data Lineage capabilities, which means confidence for the user.

How is Data Virtualization performance optimized?

The best Data Virtualization platforms employ performance optimization techniques such as intelligent caches, task scheduling, delegation to sources, query optimization, asynchronous and parallel execution, etc., for scalable performance in demanding environments.

How do Data Federation tools differ from Data Virtualization tools?

Virtualization goes beyond query federation. Some solutions provide read and write access to any type of source and information, advanced integration, security capabilities and metadata management that help achieve virtual and high-performance Data Services in real-time, cache or batch mode.

How does Data Virtualization complement Data Warehousing and SOA Architectures?

Data Virtualization can be used as an extension to Data Warehouse and other data migration solutions, federating multiple sources to create virtual Data Marts. Data Virtualization integrates with ESBs and enables real-time deployment of Data Services in SOA implementations.

What is the cost and ROI of Data Virtualization?

The investment in a standard Data Virtualization project is recovered in less than six months and its cost is one third of data replication solutions or custom developments. The ROI is obtained by savings in the cost of hardware, software, storage, development and maintenance.

How can data visualization benefit companies?

Maximizing customer engagement. Customer service is one of the most benefited from a good use of big data. Having visualization tools available has a positive impact on how companies serve their customers and solve their problems, and makes it possible to detect trends and develop strategies that better connect with those customers and potential customers.

In improving operational processes. The study and analysis of data allows to improve the automation of processes, optimizing sales strategies and improving business efficiency.

In forecasting future events. Predictive analytics is an area of big data analysis that facilitates the identification of trends, exceptions and clusters of events, and all this allows forecasting future trends that affect the business.

Prescriptive analytics. This type of analysis is primarily aimed at prescribing actions to be taken to address an anticipated future challenge. It is the next phase after predictive analytics, and can help managers understand the underlying reasons for problems and find the best possible course of action.

There are many tools available to companies to improve data visualization. From applications such as Infogram, for making infographics at all levels, to others such as Domo, an artificial intelligence-based application that allows an organization’s employees to create and share data, all of them are of great practical use in making more effective use of data, and improving decision making.

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Important Steps to Take to Address the Bias in AI

Important Steps to Take to Address the Bias in AI

We mentioned previously that bias is a big problem in machine learning that has to be mitigated. People need to take important steps to help mitigate it for the future.

Regardless of how culturally, socially, or environmentally aware people consider themselves to be, bias is an inherent trait that everyone has. We are naturally attracted to facts that confirm our own beliefs. Most of us tend to believe that younger people will perform certain tasks better than their older colleagues, or vice versa. Countless studies reveal that physically attractive candidates have a better shot at getting hired than unattractive ones. The list goes on.

We, as humans, can’t confidently say that our decision-making is bias-free. The root cause of this problem is that bias creeps in unconsciously, making us helpless in figuring out if the decisions we took were biased or not.

This is why the notion of biased artificial intelligence algorithms shouldn’t be surprising as the whole point of AI systems is to replicate human decision-making patterns. To make a functional AI system, developers train it with countless examples of how real people solved that particular problem.

For example, to build an AI system that can help sort job applications, engineers would show the algorithm many examples of accepted and rejected CVs. The AI system then would figure out the main factors that impact decisions, developers would test the system accuracy, and deploy it. In this simplified example, two problems can emerge: HR specialists can be biased in their decision-making to begin with, and the training dataset can appear unrepresentative of a certain gender, age, race, etc. For example, it can be that, historically, a company have been unintentionally hiring only men for the frontend developer position, prompting the AI to rule out women from even getting a chance to be interviewed. This leads us to the first method of eliminating bias from AI.

Data Fairness

AI has been important in solving many challenges. However, the data behind it must be well structured and as free of bias as possible.

In the majority of cases the biggest reason for AI unfairness, especially when it comes to inexperienced developers or small companies, lies in the training data. Getting a diverse enough dataset, which takes into account every demographic or any other critical attribute is what data scientists can only dream of. That’s why you should approach AI development as if your training data is inherently biased and account for this at every stage of the process.

The Alan Turing Institute has introduced a method called ‘Counterfactual fairness’, which is aimed to reveal dataset problems. Let’s get back to our example of a company that hires a frontend developer using AI. In this case, to ensure that the algorithm is fair, developers need to conduct a simple test, letting the AI system evaluate two candidates with identical skillset and experience, with the only difference being gender or any other non-essential variable. Unbiased AI would rate both of those candidates equally, while unfair AI would assign a higher score to men, indicating that readjustments need to be made.

The Institute produced a set of guidelines posed to help AI developers ensure model fairness. Here, at Itransition, we believe that such initiatives will play an increasingly important role in tackling bias in AI.

Adversarial Learning

Besides flawed datasets, bias can also creep in during the model learning stage. To mitigate this, many developers now opt for the adversarial training method. This implies that besides your main model (e.g., the one that sorts applications), you apply another model, which tries to figure out the sensitive variable (age, gender, race, etc.) based upon the results of the main model. If the main model is bias-free, the adversarial model won’t be able to determine the sensitive attribute. Data scientists cite this technique as one of the most effective and easy-to-use, as unlike conventional reweighing, adversarial learning can be applied to the majority of modeling approaches.

Reject Option-based Classification

Lastly, there is also a number of post-processing techniques that can help mitigate bias. The appeal of such methods is that neither engineers nor data scientists need to be bothered with tweaking the model or changing datasets, as only the model outputs need to be modified.

Reject option-based classification is among the most popular post-processing techniques. In essence, the bias is reduced by rejecting predictions that the model is least confident in. For example, we can set a confidence threshold of 0.4. If the prediction certainty is 0.39 or below, the system will flag the output as biased.

Team Diversity

Navigating the AI landscape depends on understanding the business context more than it’s generally perceived. No doubt, data science is closely associated with number crunching, but realizing what’s behind those numbers is equally important. And even then, data scientists’ unconscious prejudices can play a critical role in how bias takes over their algorithms. This is why, more often than not, combating bias in AI is closely tied to hiring people of different race, gender and background.

To enable more thoughtful hiring, companies need to incorporate more objective interviewing techniques. Especially when it comes to large enterprises, too many interviews are limited to traditional CV screening. Forward-looking and innovative companies now make real-world project-based data analysis a centerpiece of their interview process. Not only do they assess how well a candidate performs data analysis science-wise, but they also ensure that he or she can explain findings in the business context.

With AI being a driving force behind many business transformations, it’s imperative that we establish definitive frameworks that tackle bias in AI. It’s also important to realize that we can’t mitigate bias completely. However, it’s far more attainable to control prejudices in algorithms than in humans.

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