For several decades, before the rise of cloud computing upended the way we think about databases and applications, Oracle and Microsoft SQL Server databases were a mainstay of business application architectures. But today, as you map out your cloud journey, you’re probably reevaluating your technology choices in light of the cloud’s vast possibilities and current industry trends.
In the database realm, these trends include a shift to open source technologies (especially to MySQL, PostgreSQL, and their derivatives), adoption of non-relational databases, and multi-cloud and hybrid-cloud strategies, and the need to support global, always-on applications. Each application may require a different cloud journey, whether it’s a quick lift-and-shift migration, a larger application modernization effort, or a complete transformation with a cloud-first database.
Google Cloud offers a suite of managed database services that support open source, third-party, and cloud-first database engines. At Next 2022, we published five new videos specifically for Oracle and SQL Server customers looking to either lift-and-shift to the cloud or fully free themselves from licensing and other restrictions. We hope you’ll find the videos useful in thinking through your options, whether you’re leaning towards a homogeneous migration (using the same database you have today) or a heterogeneous migration (switching to a different database engine).
Let’s dive into our five new videos.
#1 Running Oracle-based applications on Google Cloud
By Jagdeep Singh & Andy Colvin
Moving to the cloud may be difficult if your business depends on applications running on an Oracle Database. Some applications may have dependencies on Oracle for reasons such as compatibility, licensing, and management. Learn about several solutions from Google Cloud, including Bare Metal Solution for Oracle, a hardware solution certified and optimized for Oracle workloads, and solutions from cloud partners such as VMware and Equinix. See how you can run legacy workloads on Oracle while adopting modern cloud technologies for newer workloads.
#2 Running SQL Server-based applications on Google Cloud
By Isabella Lubin
Microsoft SQL Server remains a popular commercial database engine. Learn how to run SQL Server reliably and securely with Cloud SQL, a fully-managed database service for running MySQL, PostgreSQL and SQL Server workloads. In fact, Cloud SQL is trusted by some of the world’s largest enterprises with more than 90% of the top 100 Google Cloud customers using Cloud SQL. We’ll explore how to select the right database instance, how to migrate your database, how to work with standard SQL Server tools, and how to monitor your database and keep it up to date.
#3 Choosing a PostgreSQL database on Google Cloud
By Mohsin Imam
PostgreSQL is an industry-leading relational database widely admired for its permissive open source licensing, rich functionality, proven track record in the enterprise, and strong community of developers and tools. Google Cloud offers three fully-managed databases for PostgreSQL users: Cloud SQL, an easy-to-use fully-managed database service for open source PostgreSQL; AlloyDB, a PostgreSQL-compatible database service for applications that require an additional level of scalability, availability, and performance; and Cloud Spanner, a cloud-first database with unlimited global scale, 99.999% availability and a PostgreSQL interface. Learn which one is right for your application, how to migrate your database to the cloud, and how to get started.
#4 How to migrate and modernize your applications with Google Cloud databases
By Sandeep Brahmarouthu
Migrating your applications and databases to the cloud isn’t always easy. While simple workloads may just require a simple database lift-and-shift, custom enterprise applications may benefit from more complete modernization and transformation efforts. Learn about the managed database services available from Google Cloud, our approach to phased modernization, the database migration framework and programs that we offer, and how we can help you get started with a risk-free assessment.
#5 Getting started with Database Migration Service
By Shachar Guz & Inna Weiner
Migrating your databases to the cloud becomes very attractive as the cost of maintaining legacy databases increases. Google Cloud can help with your journey whether it’s a simple lift-and-shift, a database modernization to a modern, open source-based alternative, or a complete application transformation. Learn how Database Migration Service simplifies your migration with a serverless, secure platform that utilizes native replication for higher fidelity and greater reliability. See how database migration can be less complex, time-consuming and risky, and how to start your migration often in less than an hour.
We can’t wait to partner with you
Whichever path you take in your cloud journey, you’ll find that Google Cloud databases are scalable, reliable, secure and open. We’re looking forward to creating a new home for your Oracle- and SQL Server-based applications.
Marketing strategies based on complex and dynamic data get results. However, it’s no small task to extract easy-to-act-on insights from increasing volumes and ever-evolving sources of data including search engines, social media platforms, third-party services, and internal systems. That’s why organizations turn to us at Seer Interactive. We provide every client with differentiating analysis and analytics, SEO, paid media, and other channels and services that are based on fresh and reliable data, not stale data or just hunches.
More data, more ways
As digital commerce and footprints have become foundational for success over the past five years, we’ve experienced exponential growth in clientele. Keeping up with the unique analytics requirements of each client has required a fair amount of IT agility on our part. After outgrowing spreadsheets as our core BI tool, we adopted a well-known data visualization app only to find that it couldn’t scale with our growth and increasingly complex requirements either. We needed a solution that would allow us to pull hundreds of millions of data signals into one centralized system to give our clients as much strategic information as possible, while increasing our efficiency. After outlining our short- and long-term solution goals, we weighed the trade-offs of different designs. It was clear that the data replication required by our existing BI solution design was unsustainable.
Previously, all our customer-facing teams created their own insights. More than 200 consultants were spending hours each week pulling and compiling data for our clients, and then creating their own custom reports and dashboards. As data sets grew larger and larger, our desktop solutions simply didn’t have the processing power required to keep up, and we had to invest significant money in training any new employees in these complex BI processes. Our ability to best serve our customers was being jeopardized because we were having trouble serving basic needs, let alone advanced use cases.
We selected Looker, Google Cloud’s business intelligence solution, as our BI platform. As the direct query leader, Looker gives us the best available capabilities for real-time analytics and time to value. Instead of lifting and shifting, we designed a new, consolidated data analytics foundation with Looker that uses our existing BigQuery platform, which can scale with any amount and type of data. We then identified and tackled quick-win use cases that delivered immediate business value for our team and clients.
Meet users where they are in skills, requirements, and preferences
One of our first Looker projects involved redesigning our BI workflows. We built dashboards in Looker that automatically serve up the data our employees need, along with filters they use to customize insights and set up custom alerts. Users can now explore information on their own to answer new questions, knowing insights are reliable because they’re based on consistent data and definitions. More technical staff create ad hoc insights with governed datasets in BigQuery and use their preferred visualization tools like Looker Studio, Power BI, and Tableau. We’ve also duplicated some of our data lakes to give teams a sandbox that they can experiment in using Looker embedded analytics. This enables them to quickly see more data and uncover new opportunities that provide value to our clients. Our product development team is also able to build and test prototypes more quickly, letting us validate hypotheses for a subsection of clients before making them available across the company. And because Looker is cloud based, all our users can analyze as much data as they want without exceeding the computing power of their laptops.
Seamless security and faster development
We leverage BigQuery’s access and permissioning capabilities. Looker can inherit data permissions directly from BigQuery and multiple third-party CRMs, so we’ve also been able to add granular governance strategies within our Looker user groups. This powerful combination ensures that data is accessed only by users who have the right permissions. And Looker’s unique “in-database” architecture means that we aren’t replicating and storing any data on local devices, which reduces both our time and costs spent on data management while bolstering our security posture.
Better services and hundreds of thousands of dollars in savings
Time spent on repetitive tasks adds up over months and years. With Looker, we automate reports and alerts that people frequently create. Not only does this free up teams to discover insights that they previously wouldn’t have time to pinpoint, but they have fresh reports whenever they are needed. For instance, we automated the creation of multiple internal dashboards and external client analyses that utilize cross-channel data. In the past, before we had automation capabilities, we used to only generate these analyses up to four times a year. With Looker, we can scale and automate refreshed analyses instantly—and we can add alerts that flag trends as they emerge. We also use Looker dashboards and alerts to improve project management by identifying external issues such as teams who are nearing their allocated client budgets too quickly or internal retention concerns like employees who aren’t taking enough vacation time.
Using back-of-the-napkin math, let’s say every week 50 different people spend at least one hour looking up how team members are tracking their time. By building a dashboard that provides time-tracking insights at a glance, we save our collective team 2,500 hours a year. And if we assume the hourly billable rate is $200 an hour, we’re talking $500,000 in savings—just from one dashboard. Drew Meyer Director of Product, Seer Interactive
The insights and new offerings to stay ahead of trends
Looker enables us to deliver better experiences for our team members and clients that weren’t possible even two years ago, including faster development of analytics that improve our services and processes. For example, when off-the-shelf tools could not deliver the keyword-tracking insights and controls we required to deliver differentiating SEO strategies for clients, we created our own keyword rank tracking application using Looker embedded analytics. Our application provides deep-dive SEO data-exploration capabilities and gives teams unique flexibility in analyzing data while ensuring accurate, consistent insights. Going forward, we’ll continue adding new insights, data sources, and automations with Looker to create even better-informed marketing strategies that fuel our clients’ success.
Last September, various news outlets picked up the story of an AI-generated painting taking first place at the Colorado State Fair’s art contest. To create the winning piece, the contestant entered some text into Midjourney, an online app that creates images based on text input. The result is a piece called ‘Théâtre D’opéra Spatial,’ one of the first AI-generated images to win an art contest.
While the blue-ribbon finish is a milestone-worthy achievement in AI technology, not everyone is happy. Some artists have accused him of cheating, even though the contest didn’t explicitly prohibit AI-generated imagery. Others were understandably worried that they might lose their artistic jobs to robots in the future—‘the death of artistry,’ they commented.
But this story spurs another problem. Who can be the legitimate owner of creations that anyone can create using such programs? Is the practice considered plagiarism? As it stands, intellectual property law is partly prepared to tackle this.
How AI Generation Works
Ahmed Elgammal, director of Rutgers Art and Artificial Intelligence Laboratory, explains in his article published in American Scientist that these programs employ one of two algorithm classes. The majority of these programs use generative adversarial networks (GAN).
Contrary to popular belief, some human input is still necessary for running these programs, and GAN is proof of that. The user feeds the algorithm hundreds of pictures, and the algorithm tries to imitate them as best it can. Then, the user goes through the generated images, tweaking the algorithm based on the ones they deem acceptable.
The later iteration is the artificial intelligence creative adversarial network (AICAN), which the laboratory has been developing since 2017. It takes human input out of the equation, forcing the AI to learn through the images fed to it alone. AICAN’s results have surprised researchers, as they were so accurate that people couldn’t tell that AI made it.
The Ownership Dilemma
In both GAN and AICAN, Elgammal presents an interesting thought. When his team exhibited AICAN’s works throughout the United States, people constantly asked for the artist’s name. He stressed that while he developed the algorithm, he didn’t have control over what it would do. In this instance, is the rightful artist the algorithm itself or its creator?
It wasn’t this complicated before, as the human artist would be credited even if they used tools like paintbrushes or even Photoshop. After all, these tools could only act with direct input from the user. But with AI generation, AI can make decisions regardless of human input.
Amid the lack of a clear answer to this dilemma, other AI generation programs have made steps to allow their outputs to be used for commercial purposes. OpenAI went down this route with its DALL-E 2 system, as per its announcement last July, coinciding with the creation of paid plans.
The proliferation of AI-generated creations—not just images—will profoundly affect copyright and trademark application processes. Since applying for a trademark involves searching for any conflicting application, the likelihood of stumbling upon one can increase. Businesses might get stuck in needless intellectual property conflicts—a ‘legal minefield,’ as legal experts say.
The Law As It Stands
The legal implications of AI-generated creations are slowly inspiring actions. Following the case of ‘A Recent Entrance to Paradise,’ another AI-generated work, the U.S. Copyright Office said last February that such works aren’t eligible for copyright due to the lack of human authorship. The program responsible, Creativity Machine, created it with virtually no human input.
Then, in September, media repository Getty Images followed the example of some websites by banning AI-generated content. Its official statement stated concerns with the copyright status of such works and unaddressed relevant issues as the reasons for the move. Other similar websites have done so mainly in support of human-based creativity.
In spite of these developments, some blanks in the relevant legalese have yet to be filled, namely on the matter of fair use. According to an article published in the Texas Law Review, there’s no law upholding fair use of training datasets at the moment.
As mentioned earlier, AI generation programs rely on inputted data—such as publicly available images—to produce results. AICAN was fed around 80,000 works that have embodied Western art for the past 500 years. Most of these, if not all, were made with human hands, but there’s a good chance that some have copyright protection.
Legal experts ponder the implications of AI-generated work that uses copyrighted training data. Not only is it ineligible in the eyes of the U.S. Copyright Office, but it also raises the question if it’s considered plagiarism. Is it plagiarism if a user takes credit for an AI-generated creation? Is the program committing plagiarism if it takes copyrighted work?
The AI generation programs’ developers are cautious about guarantees. According to DALL-E’s Terms of Use, the program doesn’t guarantee that it’ll work as the user intended. Others, like Midjourney, are reluctant to provide legal assistance if the work gets involved in legal trouble.
Current Legal Options
Experts say it’s highly likely that the ambiguity regarding AI-generated content will remain in the following years. According to the World Intellectual Property Organization (WIPO), as it stands, the world currently has two legal options to rely on.
The first is, as demonstrated by the U.S. Copyright Office’s decision, to deny copyright to all non-human-generated content. Apart from the U.S., authorities in Australia and the European Union have settled similar cases by rejecting copyright applications on the grounds of works not being entirely made by human hands.
The second is to credit the creator for any work generated by any AI programs. This option is evident in the United Kingdom, as stated in Section 9(3) of the Copyright, Designs and Patents Act 1988, which not only gives credit to the human creator but also grants the work copyright protection. Other countries that have taken this approach include India, Ireland, and New Zealand.
Conclusion
Intellectual property law will struggle to catch up with the proliferation of AI-generated creations in the digital age. WIPO asserts that as the technology behind the programs evolves, the fine line between human-made and AI-generated art will blur. A time will come when distinguishing the two will be practically impossible, for which the law might not have an answer.
It’s hard to overestimate the value that data insights have come to represent to today’s businesses. Investments in analytics tech have risen commensurately, with some 73 percent of respondents telling IDC that they expect to spend more on data-focused software than any other category in 2023.
While emphasizing data analytics has become the standard for the business community as a whole, smaller teams are often the exception. Small business owners are still prone to see business intelligence as a luxury that they can’t afford, as it requires employing data specialists to manage dedicated data repositories, data consolidation and ongoing coded queries – all of which is a non-starter for organizations where each team member is required to wear so many hats.
There are encouraging signs, however, that this sentiment is on its way out, and with a recession looming, small business leaders are going to need data insights to help optimize their strategies.
Many specialized data tools are now available as self-service web apps, making enterprise-grade data software more affordable and circumventing the need for dedicated servers. The expertise barriers have also been lowered, with onboarding rendered simple and quick – today, even non-data experts can set themselves up and make data-based strategic decisions on an ongoing basis.
With a better understanding of what the advantages analytics bring, small business owners are finally getting started with business intelligence.
Consolidating Information
Analytics gives business owners an accurate picture of the state of their ventures. Fortunately, businesses are likely already gathering data from the various business apps they use. All this information can be imported to analytics tools for processing.
Modern business intelligence platforms can integrate with hundreds of data sources like marketing communication tools, ecommerce platforms and payment providers to create this holistic picture. Business leaders can then consolidate whatever performance metrics matter most to them into dedicated interactive dashboards and dynamic reports.
Businesses that use cross-functional management suites can also explore their built-in analytics tools. Business management app vcita, which allows small teams to handle client relationship management, payment collection, appointment booking and marketing activity under one platform, uses Google’s Looker BI software to generate reports from specific operational areas that already flow through the app.
For example, a service business owner can examine their appointment conversion data to check which services are the most popular or how many customers follow through with each booking. By analyzing these specific areas of the business, entrepreneurs can readily spot issues and implement improvements.
Visualizing Trends and Extrapolating Predictions
Traditionally, it takes a certain level of specialized expertise and experience to make sense of raw numbers. What makes analytics accessible to most people is visualization. Modern tools can readily create charts and graphs to help users spot trends from their data.
The only thing that small business owners have to do is integrate their apps with visualization tools. The cloud version of Tableau, for instance, allows non-technical team members to use native “connectors” to import data sources like Salesforce, QuickBooks and Amazon Seller Central, helping merchants visualize data based on historical sales figures.
By plotting line charts of monthly sales for products, it’s possible to identify peak seasons and top-performing items. These insights can then be used as the basis for promotions and marketing campaigns.
Analytics can also be predictive. Through machine learning, even basic tools can crunch historical data and provide predictions readily. Combined with visualization, analytics can help owners of even the smallest businesses to plan for the immediate future, like increasing inventory to prevent stockouts during peak sales.
Performing Analysis in Natural Language
Analytics platforms are constantly innovating to further lower barriers to entry. Developers use effective usability design and artificial intelligence so that non-experts can perform data analysis capably.
By applying artificial intelligence, platforms can allow users to use natural language to interact with analytics platforms. Intelligence platform Phrazor, for example, allows for queries to be phrased using simple questions. Keying in a question such as, “Why did my sales grow in the last six months?” can bring up sales data within the period and the possible answers to the query.
Inversely, natural language report generation is now also emerging as a standard. Alongside visualizations, reports with accompanying insights can be generated in natural language, allowing less data-savvy business owners to create easily understood reports quickly.
Making Key Decisions Using Data
According to the Small Business Administration, about two-thirds of new businesses survive in their first two years. Armed with a clear picture of the states of their companies, entrepreneurs can quickly pinpoint whether they are poised for survival or growth. They can decide which business areas to focus on to improve their standing or pivot their business if necessary.
Through analytics, business owners can base their decisions on solid information – or, at the least, validate their intuition.
While today’s business environment is volatile to say the least, specific sectors and niches are still projected to be growth industries, providing opportunities to smarter owners of small businesses. Through business analytics, small businesses can create viable strategies to navigate their respective markets and position themselves to thrive and succeed.
Machine learning technology has transformed countless fields in recent years. One of the professions affected the most by advances in machine learning is mobile app development. The market for mobile artificial intelligence is projected to be worth nearly $9.7 billion within the next five years, since machine learning helps developers create powerful new apps.
We have talked extensively about some of the benefits of AI and machine learning in mobile app development in previous blog posts. However, one of the benefits that we haven’t talked as much about is the application of machine learning for testing new apps during the design process. Apps need to be carefully tested, so it is important to use the right strategies to do so.
App developers can find novel ways to use machine learning to automate the testing process. This can reduce the costs of app development and help them spend more time on other essential tasks.
Machine Learning Enables App Developers to Automate Essential Processes Like Testing
In the past, mobile applications were much more straightforward and had fewer features than the mobile apps we know today. As the features increased and the functions of the apps became more intricate and complex, the app testing process required adaptation to meet the requirements of the modern applications.
Testing of applications nowadays can be done manually or automatically, but in the past manual testing was the only way. As the features of the apps increased and became more enhanced, manual testing became extremely timeous and difficult. This is one of the main reasons app developers use AI and machine learning.
This is where automated mobile app testing became the way to go for modern apps with more features and capabilities and only 13% of app developers reported that they only use manual testing. App developers use test automation to enhance app testing processes and to simplify the entire testing process.
Companies like HotShots Labs use automation testing tools for all the mobile applications that we develop to ensure we provide the highest quality applications to our clients. They are able to accomplish this process with the use of advanced machine learning algorithms. Machine learning has helped them streamline the process considerably.
1. What Is Automated Mobile App Testing?
Automated mobile app testing refers to the evaluation process that mobile app developers should run through for each application that they develop to ensure the mobile apps perform correctly before publishing. The process relies on advanced machine learning algorithms that help make the process go more smoothly and rapidly.
There are various test automation frameworks that developers can choose from to find the perfect mobile testing framework for their specific application and to evaluate how it will operate on different mobile devices and on different operating systems such as Android and iOS.
How do testing tools that use machine learning work? Mobile app testing tools are used to run through the entire operation process of the application using a test script as if it were a user operating the application. In this way errors and bugs are picked up, and can be fixed or updated to ensure efficient operation of the mobile app.
The testing tools run through different test scenarios and test cases to detect any errors that might be in the development code of the mobile application, and therefore these automation testing tools are extremely beneficial and developers, therefore, rely heavily on automatic mobile testing.
2. 7 Benefits of Automating Mobile App Testing with Machine Learning
There are a number of reasons that app developers may want to use machine learning technology to automate the testing process. Some of the biggest benefits are listed below.
Enhance Publishing Timeframes:
repetitive operations are automated throughout the mobile app testing process, saving a lot of time, and accelerating the test execution process.
Enhance Application Functionality:
Automated mobile app testing thoroughly validates app functionality and makes sure there are no faults or flaws that might affect it. Thus, it allows mobile apps to operate efficiently.
Enhance App Security:
Security flaws in mobile apps can result in the theft of client information and reputational damage to enterprises. Security flaws in a mobile app can be easily spotted and fixed by using the right mobile app testing strategy and mobile automation framework.
Improved Application Performance:
Several performance tests are done during automated mobile app testing to make sure there are no performance holdups in an application and that it functions properly under all user loads.
Boosts App Loading Speed:
Mobile app developers must offer quicker loading times for both Android and iOS apps since slow mobile app loading speeds negatively affect user experience. By eradicating flaws from the app, automated mobile app testing provides a quicker download time.
App Multiple Platform Compatibility Verification:
This ensures that the mobile apps are compatible with multiple operating platforms and software to boost user experience. App integration tests are also run to ensure sufficient performance.
Boosts Cost and Time Efficiency: Test automation of mobile applications protects brands from abrupt app failures or crashes, saving enterprises a significant amount of money and preserving their good name. Automated testing also ensures that testers do not have to allocate their time towards tedious and repetitive duties. It also guarantees that tests are run faster.
3. How to Use Machine Learning to Automate Mobile App Testing
Here are a few things that you need to do when you are trying to automate the mobile app testing process with machine learning technology. You want to follow these steps carefully.
Establish Automation Test Plan
This step is completed by developers by creating a plan on which devices will be used in the testing phase and what specifications the devices should have. This plan will also include the type of testing that will be conducted and will be detailed at a later stage in the testing process.
Create Test Scripts and Test Cases
This is a crucial step as this will set out the exact functionalities and operations that the test should focus on. These scripts and cases can be used multiple times for different testing operations as it is a base followed by developers in the testing process.
Establish Mobile App Test Setting
In this step developers need to install the application that needs to be tested on the right devices, and developers should ensure that testing data can be monitored and revisited for enhancement and amendment purposes.
Proceed with Testing
In this step the developer will action the testing process through the automated testing framework. The mobile app test automation framework and tools will then perform the tests based on the type of testing required as stated in the first step. These types of tests can include Functional testing, Continues Testing, Usability testing, UI testing, User acceptance testing, Performance and load testing, Security testing, Accessibility testing, and Digital testing.
Use Machine Learning to Automate Mobile App Testing Strategically
There are many benefits of using machine learning in the mobile app development process. One of the top benefits is that it can help automate testing. Automated mobile application testing provides numerous benefits and if the testing done correctly and the right steps are followed, at the end of the automated mobile app testing process you should have an app that performs effectively and will therefore be ready for the big launch.
The demand for AI and data science professionals is growing all over the world. Many data scientists are pursuing careers in Europe and Asian, which means that they have to be aware of the opportunities and requirements abroad.
Italy is one of the most promising countries for people seeking careers in data science. Italian employers spent $78.3 billion on big data last year. This figure is expected to grow as more companies discover the benefits of investing in big data and AI.
However, Italy also requires data scientists and AI programmers to possess the right credentials to seek employment. You will need to make sure you are familiar with them before you can get a job as a data scientist.
Italy is Home to a Growing Market for Data Scientists
As the global financial situation becomes increasingly concerning, many businesses are turning to technology to shore up their foundations. Small businesses are using data analytics tools to cut their expenditure, while some large firms are exploring international options when it comes to tech innovation.
One of the newest arrivals on the scene, with a multi-city tech ecosystem that is just beginning to come of age, is Italy. Its cities do not yet have the long-term tech credentials of established centers such as London, where tech companies raised $18.4 billion in 2021, or Berlin or Paris. However, a number of Italian cities are growing fast in terms of their tech scenes.
At present, Italy’s tech scene is on a par with Latvia’s in terms of its development. It has attracted some of the best data scientists in the world. Both countries have nurtured their first unicorn during 2022. Latvia’s was print-on-demand group Printful, which raised $130 million, while Italy’s was fintech start-up Scalapay, which raised $497 million in Series B funding. In total, investments in tech start-ups in Italy equated to around €1.4 billion in 2021.
Home-grown talent
When it comes to tech talent, Italy is punching well above its weight. Some 12% of Europe’s top tier AI researchers come from Italy, despite the fact that Italy accounts for just 8% (approximately) of Europe’s population. The country is also home to some of the best data scientists in Europe. The country is attracting an increasing amount of venture capital funding to its tech scene and has begun capturing the attention of the international community.
Rome (Italy’s capital) and Milan (the country’s financial center) have rapidly established their tech scenes in recent years. They have invested heavily in big data, as they try to find new ways to scale economic growth and boost technological progress. Milan is currently developing an entire tech district, with not just workspaces but also a start-up accelerator and research labs. Padua, in the northern Veneto region, meanwhile, is the latest newcomer. This city is a semi-finalist in the European Rising Innovative city category of the European Capital of Innovation Awards (iCapital) 2022.
Tapping into Italy’s Tech Scene to Discover Qualified Data Scientists
If your business is one of those drawn to Italy’s blossoming tech scene to find some talented data scientists or AI programmers, it’s time to take on board some tips around language and culture. Italian workers are known for putting in long hours and for being both focused and productive at work. They also value the social side of business interactions, developing personal connections within the hierarchical framework that still typifies much of Italian working life (though Italy, like many other countries, is seeing its rising tech entrepreneurs take a less formal approach to working life).
In language terms, any business looking to get involved in Italy’s tech scene will do well to partner with an Italian translator that they can rely on. English to Italian translation (and vice versa) will be a regular, ongoing requirement. What is the best Italian translator? It is a service that delivers tech expertise alongside Italian translation. Translating tech documents requires technical knowledge. According to language services provider Tomedes, whose native Italian translators have translated thousands of documents for official and professional use, that means sourcing an Italian translator with relevant experience who understands technical language and concepts, as well as the particular nuances of the Italian tech scene.
Tomedes’ highly tech-savvy, tech-driven translation expertise has satisfied many clients over the past 15 years, including major players in digital industries, such as Amazon, Microsoft and Google. Key to its service delivery is an in depth understanding of the Italian language, including those words such as gattara and abbiocco, which have no direct translation in English (the former is a woman who takes care of stray cats; the latter a sudden desire to sleep after a hearty meal). The company has used some of the most sophisticated big data tools to expedite its service delivery.
How do I choose a good translation service? Firstly, keep those technical requirements front of mind. Next, ask the agency who it is that will translate Italian for you. It should always be native speakers of the target language – so if you need English to Italian translation, it should be native Italian speakers delivering your documents. Likewise, if you need an Italian to English translation service, it should be native English speakers who undertake the work. They have a number of AI and big data algorithms that make the job go by more quickly.
It’s also important to look for a translation service with experience of business and marketing translation. Your Italian translation needs likely won’t relate solely to technical documentation. Instead, you will need to connect with other businesses, working out supply chain logistics, manufacturing deals and more. You will also need to market and/or advertise your products, whether through social media, content marketing, pay-per-click advertising or myriad other channels. It’s likely you’ll need legal translation at some point too – particularly around contract law or employment law – so be sure to factor that into you plans.
For each of these tasks, you will need not just a qualified linguist, but an Italian translator with relevant experience. So, when you’re choosing a translation service, be sure to grill the agencies you speak to on the breadth of their experience, not just their language expertise.
Given the explosion of interest in Italy’s tech scene over the course of 2022, the stage has been set for the country to achieve big things in 2023 and beyond. It’s the ideal time for forward-thinking businesses to engage with the Italian tech marketplace and be a part of the country’s future. The fact that the Italian Ministry of Economic Development began awarding €45 million worth of funding in September 2022 for certain blockchain projects, of course, may also be a powerful reason for your business to set its sights on a future venture in Italy.
Data Scientists and AI Programmers Are Discovering New Opportunities in Italy
Italy is home to a thriving tech sector, which has attracted countless data scientists in recent years. Anyone in this profession should consider relocating to this Mediterranean country. However, they must be familiar with the credential requirements first.
Artificial intelligence is playing an important role in modern creative professions. There are a lot of reasons a growing number of companies are turning to AI technology. One poll showed that 61% of companies found that AI and machine learning were their best data investments.
Here is a fact that you should consider. According to content marketing statistics, 32% of marketers say visual images are the most important form of content for their business, which is probably why you’re here. AI is crucial to helping these companies use these new images.
How AI is Changing the Nature of Web Design
Mirza Irfan of Usability Geek discussed some of the benefits of AI in web design. These benefits include improving UX and creating ADI (artificial design intelligence) solutions).
If you’re a web designer or web developer, your job is to work to make a website functional and attractive. You must consider the user experience (UX) every step of the way.
If you are not sure where to start when creating awesome eye-catching visuals for your digital marketing, then you should keep reading. You will find out why AI is helping companies meet these standards.
The best way is to synthesize all that information down to these four basic design principles:
Contrast
Repetition
Alignment
Proximity
These principles predate the existence of AI. However, AI is helping designers reach them more effectively.
These concepts do not just apply to web design and UX, but rather anything you want to make look smooth, clear, and eye-catching (i.e. graphics, blog articles, and Facebook ads).
By the end of this article, your site will have an ace up its sleeve in design. You’ll have a secret hand to trounce the visual competition by providing you with effective principles to enhance your visual content.
The Three Stages of Design with AI: A Formula for Visual Success
When figuring out the visual design of a website and the ways to leverage AI to achieve it, the design process can be broken up into three parts:
Target Research: Researching and thinking about the target audience.
Strategic Goals: Understanding the company goals and how the goals impact the user.
Creative Design: Applying creative design thinking to develop a smooth and enjoyable end-user experience.
What Does It Take to Master the Principles of Design in the Age of AI?
The short answer? Not as much as you think!
You will find that there are a number of new AI tools that simplify the process. This helps reduce the need to be a skilled designer. The AI algorithms can do a lot of the heavy lifting for you.
Web designers often have a background in graphic design, art, advertising, or another creative discipline. But AI is becoming a more important competency.
However, as marketing teams become smaller, professionals of different backgrounds have had to take over the responsibilities of graphic designers. They use easy design tools online like Canva and Visme to create custom graphics.
Trained web designers or creative marketers alike should always focus on the actual needs of the people you are designing for, a.k.a. be human-centric in your website design.
This makes for a simple and enjoyable user experience.
4 Basic Visual Design Principles
Here’s where we get to the juicy material: contrast, repetition, alignment, proximity. These 4 basic design principles will make sure your content has good UX, no matter the graphic. Your website will be visually stimulating to visitors and leave a memorable, positive impression.
1. Contrast
Contrary to popular belief, web designers can contrast more than colors. This includes:
Shading: Light vs. Dark
Size: Big vs. Small
Patterns: Solid vs. Ornamental
Fonts: Serif vs. Sans serif
Color: Complementaries, Adjacents, Triads
Themes: Symmetry vs. Asymmetry
Texture: Rough vs. Smooth
Check out the example below to see how the contrast between light and dark is used to draw attention to the form fields in a website popup:
Here’s my number one suggestion for employing contrast:
Establish a brand color palette carefully and early.
Browsing existing color palettes on Adobe Color is extraordinarily helpful. You can determine specific hex codes, proper combinations, etc. You can even use the Adobe Color software to dissect the exact colors inside existing images if you found a color online that you are dying to have!
The image above is a user experience example of contrasting colors to guide readers’ eyes where the designer wants them to go.
What are the first things your eye catches? Is it first the image, then the heading, and then the button?
If so, the Taab web designer who created this was successful.
2. Repetition
Repetition is an important element of web design that automates the user experience. It makes going through your webpage faster and easier because users do not have to constantly go back to get to a different page. For example, a web designer should always include the main menu for a website on every page to allow the user easy access to all pages on the website.
Backtracking runs the risk of losing visitors and having them click off their page due to complexity or laziness.
Always make the user experience and simple and smooth as possible!
In addition, visual repetition also contributes to:
Unity
Consistency
Memorability
In psychology, the fact that our brains rarely need to hear the whole message before putting the pieces together is called heuristics. Repetition contributes to this phenomenon by calling on a user’s memory to fill in the missing parts.
In other words, the user knows what to expect. Repeating elements contribute to building the big picture a lot faster. Your user will be able to understand a graphic or navigate a website if they’ve been exposed to a similar design or pattern for that content.
Keep consistency throughout your website to maximize the user experience. If the menu bar is on the top-right corner of one page, make sure it is in the same spot on every other page.
Alignment is not just good for your back, it is good for your UX design!
That’s because alignment accomplishes the following:
Sets a hierarchy
Makes your design orderly
Adds a sense of professionalism
Alignment is one of the most vital design principles for beginners and the top tool for effective alignment is grids. Grids work very well in helping web designers maintain spacing between objects so as to not overwhelm the user with too many elements on a page.
Check out the example below for an example of how a web designer can use grids to organize the layout of a webpage:
Without alignment, your website can look unprofessional and lack order. It runs the risk of looking amateur and unattractive. Equally bad, your users will be confused and click off the page.
You want your website to be cohesive and for all of the elements (buttons, text, graphics, etc.) to be aligned neatly and consistently.
Horizontal alignment includes:
Flush-left (also called left-justified or ragged right)
Flush-right (also called right-justified or ragged left)
Centered
Fully justified
With vertical alignment, elements can be aligned vertically, which includes top, bottom, or middle (center).
Here’s a PRO TIP:
Ignore the little voice inside telling you that you can fit just one more thing and go for a “clean” design!
Design aspects you can align:
Labels
Headers
Margins
Rows and columns
Buttons and icons
Graphics
Text
4. Proximity
Last, but not least, we have proximity. Here’s a breakdown of what proximity does:
Connects Elements: Objects that are closer together are more likely to go together in the user’s mind.
Finishes Ideas: Using heuristics in proximity lets the design fill in the blanks for a reader.
Accelerates Understanding: Design elements that are close together speed up the comprehension of the reader.
Interestingly, the design principle pf proximity is relatively unknown compared to big-name principles like contrast.
Of course, these ideas are meant to be used in conjunction, but if you absolutely had no way of employing contrast, you could still get your point across with the principle of proximity.
Often, proximity is best combined with repetition to form consistent spacing between particular sets of elements.
If you need help planning out the structure of your design, you could use the golden ratio, which leverages proximity to maintain balance.
Here’s an example of the golden ratio at work:
AI is Changing the Nature of Web Design
AI is changing the role of web design in crucial ways. It couldn’t have come at a better time, because having a user-friendly website is more crucial than ever. You need to ensure your business gets the attention it needs. Keep visitors on your page by incorporating these design tips in every aspect of your website. By employing contrast, repetition, alignment, and proximity into the user interface, yourself, web designers and developers will be able to increase the user experience and ultimately drive conversions on your website.
AI technology has been invaluable to the financial industry. The amount of money that fintech companies are spending on AI is projected to grow by 16.5% a year from 2022 and 2030.
AI is changing the alternative financial sector as well. For example, many bitcoin investors are finding creative ways to use AI to improve their trading strategies. In fact, AI has played a key role in the growth of bitcoin popularity.
What Are Some Ways that You Can Use AI in Your Bitcoin Trading Strategy?
There are a number of ways that you can use AI technology to improve your bitcoin investing strategy. Here are some ideas.
Use AI to Automate Your Trading Strategy
One of the biggest benefits of AI is that it can automate your bitcoin trading strategy. AI-driven trading systems like Immediate Edge have made trading easier than ever. As we stated before, AI-based bitcoin trading can disrupt the bitcoin market.
AI-based trading systems help you take advantage of the volatility of the cryptocurrency market and make large amounts of profit. The software uses multiple market parameters and critical market data to break down and analyze market movements. AI-driven bitcoin trading application can perform all the heavy lifting for you, from speculating on market fluctuations to taking out profitable trades and executing them.
You don’t have to do anything because all the work will be done by the system itself. Just sit back and enjoy or monitor your profits. The algorithm technology has great accuracy in detecting market rates to give you peace of mind for investing. This bitcoin robot provides the same opportunities to both experienced and inexperienced.
The process is very simple, the software buys the most active cryptocurrency of each moment and sells it when it increases in value. Before selling an asset, the algorithm takes into consideration the price of that asset on all cryptocurrency exchanges and sells it on that exchange where its price is higher.
Predict Price Movements with Predictive Analytics
AI has also led to the inception of predictive analytics technology, which can also help bitcoin investors. Predictive analytics algorithms are able to evaluate a number of different variables and identify future price movements. This can help you take advantage of market inefficiencies.
Since bitcoin is a much less efficient market than stocks and bonds, it is a lot easier to exploit new information to make a profit. AI-driven technology can help if you are willing to invest in predictive analytics.
What Are the Benefits of Using AI as a Bitcoin Investor?
There are plenty of different reasons you may want to consider investing in Bitcoin. These benefits will be even more significant if you are willing to invest in AI technology to support your bitcoin trading strategy. Some of the arguments for buying Bitcoin are listed below.
Inflationary Hedge
One of the main reasons to consider buying Bitcoin has to do with there being a finite number of Bitcoin out there. Whether fiat currency always has an inflationary risk because more can always be printed. Monetary and fiscal policy can drive the overall value of the dollar to decrease. You can boost your returns even more by using AI, which makes it an even better inflationary hedge.
Limited Supply
Bitcoin will never have this inherent risk attached to it. There are only 21 million bitcoins and as many as 3.7 have been likely permanently lost. As a result, there’s only going to be 17.3 in circulation at any given time.
Transactional Usage
AI isn’t the only new technology that is helping with bitcoin trading. Blockchain is also extremely important for cryptocurrency investors.
There is a lot of hope that one day Bitcoins will be used for transactions on a wide scale. As Bitcoin gets increasingly mainstream, it can be used for more and more transactions whether you are paying for a movie ticket or something else. It’s getting more mainstream attention as you’ll find it showing up on popular and widely used financial sites alongside the stock market and precious metals.
Bitcoin is inherently more secure because of its blockchain technology. The blockchain technology used in Bitcoin is completely decentralized. Thus, it makes for a much more secure way to complete transactions. This also allows for transactions to go smoother without middleman interference and fees being imposed.
Digital Gold
There is a lot to like about Bitcoin having a finite supply. Because of this, it’s been seen as the digital version of gold. Being compared to gold is always a plus because gold has been a tremendously stable store of value dating back to 550 B.C. While Bitcoin is relatively new in comparison, it’s much easier to use in day-to-day transactions than gold has ever been with the use of a crypto trading app.
As you can see, there are plenty of strong arguments as to why Bitcoin could be a good investment decision. However, there are equally as many reasons not to buy Bitcoin and these arguments could be considered even stronger. These include:
Bitcoin Is Overbought
One of the things you don’t want to do is buy at the peak of bull markets. Bitcoin is up a lot over the past 5 years or so. Because of this, you could be buying way too high which can expose you to a lot of unnecessary risks. Since May 19, 2020 Bitcoin is up 7,876%.
You will want to use AI-driven trading strategies to better anticipate future price movements, so you can purchase at the right time.
The Risk to Reward Is Skewed
One of the biggest reasons to avoid buying Bitcoin right now is because it’s priced too high that the risk-to-reward ratio is skewed. Bitcoin cannot continue to surge in value as it has in the previous 5 years. While it’s impossible to predict the price movement of any asset, it’s reasonable to expect Bitcoin’s value to not continue going up in a straight line. If it continued to grow as it did in the previous 5 years, it would put the total value of Bitcoin at $88 trillion in only 5 more years. This is nearly impossible to think about considering that’s over 4 times the USA’s Gross Domestic Product for the year 2020. It’s simply not going to happen and the mania days resulting in exponential growth are likely over.
There’s More Competition
In the earlier days, Bitcoin was one of the only cryptocurrencies out there generating a lot of appeal among investors. Nowadays, you will find a lot of cryptocurrencies available and there are limited barriers to entry for making new ones. This has led to the entire market being flooded with cryptocurrencies. For instance, Dogecoin was created as a meme and it achieved a $43 billion valuation as of May 18. Ethereum is another that has a value nearing half of what Bitcoin is worth. And Ethereum utilizes a similar decentralized payment network and has other applications like smart contracts that make it highly intriguing.
The Crackdown Could Happen At Any Moment
Global governments can crack down on the cryptocurrency market at any time. It’s an unregulated space. A lot of governments could eventually ban cryptocurrencies. The crypto space already has the IRS’ attention.
Hyperinflation Fears Have Always Been There
There’s always been this talk about hyperinflation and about how the value of the dollar is going to tank and plummet. However, to this point, it has never occurred. A lot of people have been investing in precious metals like gold because of this with minimal returns.
The Volatility
Bitcoin is easily one of the most violative assets out there. Bitcoin can make the stock market look stable with how volatile it is. Cryptocurrency is a pure speculation play at this point and not many people want to put their money into something that carries so much risk.
AI Technology is Changing the Future of Bitcoin Trading
A growing number of bitcoin investors are taking advantage of the benefits of AI technology to improve their strategies. AI-driven trading can help bitcoin investors boost profitability considerably.
Although the COVID-19 pandemic was one of the greatest challenges the world has ever endured, it is important to acknowledge there were some notable advances in the fight against the infectious virus. Big data and AI technology have played a huge role in dealing with some of the challenges that arose. We previously talked about the benefits of big data and BI in overcoming the problems the pandemic caused for businesses. However, they were even more important when it came to dealing with public health concerns.
Consider that throughout the fight, many leading technology companies and other well-known parties have been using big data and AI technologies in new and innovative ways to help Public Health officials meet the challenge of COVID-19 since the outbreak’s inception.
Vaccine Matching Programs
One doctor recognized the high volume of vaccines that went to waste, despite many parties needing them. The resulting Dr. B platform allowed clinics with vaccines and people who wanted them to register and connect. Unlike the previously available state websites, this technology was simple for anyone to use. It used big data to better understand the needs of patients on an individual level and match them with the vaccines that they needed.
Anyone could join the waitlist by providing basic contact information and details about their eligibility in the state, such as employment and pre-existing health conditions, on a simple registration page. The website used state parameters to continuously readjust algorithms and suggest vaccine availability to only those who met their state’s requirements. This wouldn’t have been possible without major advances in big data technology.
3D Printing Helped Produce Nasal Swabbing Kits
One example is evident in the actions of the 3D printing community, which also wouldn’t have evolved without advances in AI and big data technology. Throughout the pandemic, one of the major issues confronting the healthcare system was a lack of tests and medical supplies such as Personal Protective Equipment (PPE). Companies like NASCAR donate 3D printing equipment and technology to Ford and Toyota to address the medical supply shortage. Other companies used their 3D printers to produce nasal swabs for Covid-19 testing.
Additionally, 3D printing is also helping to manufacture medical equipment such as ventilator valves and emergency respiration devices, as well as personal protective equipment (PPE) such as masks and mask fitters. AI and bigdata have helped improve the effectiveness and efficiency of 3D printing tools.
Big data and artificial intelligence (AI) have also shown advancement in detecting and monitoring infectious viruses. For example, one artificial intelligence company released free COVID-19 analysis software for early virus diagnosis and assessment. The software could detect, segment, and generate 3D models of lung damage caused by the virus by using CT image analysis.
In addition, contact tracing in certain offerings could combat the coronavirus outbreak via mobile technologies such as GPS, cellphone masts, and AI-powered big data analytics to assist the government in understanding and managing the spread of COVID-19 within their communities.
Some tools were even able to use AI to monitor the spread of COVID-19 and predict where and when outbreaks might occur. AI-powered chatbots also gained popularity in use cases designed specifically for travellers. The mobile app could inform and assist with coronavirus-related questions as people moved around.
Online Technologies Paved Way For At-Home Education
Another way technology helped fight the pandemic was through the support of online initiatives. During the pandemic, the world met a variety of online platforms available to connect students and workers to their schools and offices from home. Educators in China, Colombia, Italy, Jordan, South Korea, Spain, Uganda, and the United States embraced online learning. They conducted live-streaming classes using digital platforms such as Alibaba’s DingTalk, Google Hangouts, Kolibri, and Microsoft Teams.
Businesses worldwide are using video conferencing and screen sharing on electronic devices via digital platforms to bring their teams together without needing to be in person.
Improving Patient Care with the Internet of Things
Healthcare providers are already using the Internet of Things (IoT). With IoT, patient imaging, health devices or applications, worker solutions, and ambulance programs could help improve treatment plans for the public. However, COVID-19 forced the technology to adapt to new applications to assist the world in combating the epidemic.
Some examples were tracking quarantine, pre-screening and diagnosing, cleaning and disinfecting, innovative drone use, and reducing in-home infections.
Mobile Apps With Up-to-Date-Information
Mobile apps were another notable technology that changed the game amid the COVID-19 pandemic. Before the pandemic, mobile apps were already looking for ways to help patients receive online therapy, at-home testing, complete self-checks, and improve their mental health. Following the pandemic, the world saw an increase in their usage, making it possible to track the virus’s path and help limit its spread.
In a more specific example, one application contained vital and relevant information on the coronavirus pandemic from trusted sources, such as hand hygiene practices, social distancing FAQs, quarantine guidelines, self-checking tutorials, and cleaning and disinfecting surface tips. The same app included a screening tool that advised the world on what to do if they had or came in contact with someone with COVID-19 symptoms who had recently returned from abroad.
Big Data and AI Have Been Invaluable for Dealing with Challenges During the Pandemic
Despite the coronavirus pandemic now being in the endemic stage, we still see the effects of the disease lingering. However, those issues would have been much worse without interventions that were made possible with AI and big data.
Furthermore, while some of these effects caused enormous damage, others have driven the medical industry forward. Throughout this blog post, we noted how many tech innovators accelerate improving medical treatment with IoT, AI and mobile apps.
Although smart technologies cannot replace or compensate for public institutions’ measures, they play an important role in emergency response. A reality we see today.
Proper marketing and sales prospects play a huge role in improving the success rate of your business. The strategy can either be offline or digital. However, digital marketing has become the major focus of marketers across all industries, mainly due to how customers interact and engage with modern businesses.
Seeing an opportunity and knowing how and when to take advantage of it defines the majority of where today’s marketers stand. To develop effective and optimized strategies in this ever-changing marketplace, a smart marketer needs to know how to leverage technology. Enter Big Data. Although big data isn’t a new concept, it has become a sought-after technology in the last few years.
The following blog discusses what you need to know about big data. You’ll learn what big data is, how it can affect your marketing and sales strategy, and more. Keep reading.
What Is Big Data?
Big data refers to an extremely large volume of data sets, including structured and unstructured data from several sources. The big data is so vast that it’s hard for outdated data processing techniques to capture, manage or process the data sets. However, with the right software, it’ll be easier to process the data sets, addressing previously inaccessible business problems.
Basically, big data has three characteristics: variety, volume, and velocity. In other words, the data sets contain great variety, coming in increasing volumes with high velocity. The data sets can come from publicly accessible sources such as the cloud, social media, and sites.
A business can utilize the data sets to access customer details such as likes, interests, purchase history, and more. Examining this crucial data makes it easier to develop personalized techniques to improve your marketing effort.
Also, if you’re dealing with other businesses, you can employ big data analytics tools to examine b2b data and find out information such as hidden patterns, market trends, and more. Hence, you’ll develop a marketing effort that beats the competition, improving your future sales and brand awareness.
How Can Big Data Revolutionize Future Marketing And Sales?
The following are the reason why big data is the future of marketing and sales. They include:
Better Insights
This is one of the ways big data can revolutionize future marketing and sales. Developing deeper insights into your target audience can take time and effort for most businesses. The concept of knowing your customer (KYC) was initially used by financial institutions to prevent bank fraud.
However, with big data, it’s easier to access crucial KYC data such as customer preferences, purchase history and patterns, likes, and more. Whence, it’ll be easier to develop personalized marketing efforts, improving their effectiveness and leading to increased sales.
Additionally, it’ll be easier to understand how customers view and interact with your brand, improving business intelligence. Improved business intelligence allows you to bring about positive changes, such as improving existing products.
Help Increase Conversion Rate
This is another way big data might revolutionize marketing strategies. As discussed above, big data might help you develop deeper insights into your customer. Hence, it’ll be easier to understand what they need and why. Understanding customers’ behavior makes it easier for businesses to develop strategies that meet their needs and expectations, increasing the chances of conversions.
Also, big data makes it easier for marketers to know when to respond to leads. Failure to respond at the right time may affect your conversion rate, affecting the overall sales and revenue. However, applying the insights of big data analytics in all areas of marketing makes it easier to respond at the right time, increasing the conversion rate.
Making Pricing Decisions
Your pricing decisions may affect the effectiveness of your overall marketing effort. When using basic data sets, you will need more information to make the right pricing decision. However, big data allows you to access crucial information such as incentives, completed deals, competitor pricing, product cost, demand, value, and more. You can use these data to achieve clarity in pricing, which can be crucial in the business-to-business (B2B) sector.
Additionally, accessing crucial customer and current economic status may provide valuable insights into pricing. Thanks to technological advancement, you can also integrate advanced solutions such as automation to improve accuracy and reduce errors in your pricing process.
Also, big data can help you access ever-changing information such as exchange rates, government spending, growth rate, and other data which are crucial when making the correct pricing decisions.
Bottom Line
As discussed above, big data has become a crucial aspect of modern marketing and sales prospects. However, before integrating this technology into your marketing efforts, it’s important to understand how it might boost your strategy. Conduct extensive research to ensure you’re equipped with the necessary know-how, giving you value for your money.
