TERRACOTTA DB: FASTEST FOR IN-MEMORY DATA

| August 29, 2018

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The volume of data ingested into our systems is only going to accelerate with the Internet of Things (IoT) and tighter app integration on mobile devices like smartphones. The challenge is not just ingesting that data but using it to deliver meaningful insights to the business and trigger actions with the lowest latency possible. Here’s where Terracotta DB excels.

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Zylotech

Zylotech is a Self-Learning customer data platform for marketers. Imagine having a 360-degree view of your customers on demand including their identity, behaviors and intent; Insight to non-obvious patterns of information only available through the latest AI models; Automation personalizing customer recommendations for you in the tool of your choice. This is the Zylotech advantage - bringing cognitive customer intelligence to your fingertips.

OTHER ARTICLES

Exploiting IoT Data Analytics for Business Success

Article | January 21, 2021

The Internet of Things has been the hype in the past few years. It is set to play an important role in industries. Not only businesses but also consumers attempt to follow developments that come with the connected devices. Smart meters, sensors, and manufacturing equipment all can remodel the working system of companies. Based on the Statista reports, the IoT market value of 248 billion US dollars in 2020 is expected to reach a worth of 1.6 Trillion USD by 2025. The global market is in the support of IoT development and its power to bring economic growth. But, the success of IoT without the integration of data analytics is impossible. This major growth component of IoT is the blend of IoT and Big Data - together known as IoT Data Analytics. Understanding IoT Data Analytics IoT Data Analytics is the analysis of large volumes of data that has been gathered from connected devices. As IoT devices generate a lot of data even in the shortest period, it becomes complex to analyze the enormous data volumes. Besides, the IoT data is quite similar to big data but has a major difference in their size and number of sources. To overcome the difficulty in IoT data integration, IoT data analytics is the best solution. With this combination, the process of data analysis becomes cost-effective, easier, and rapid. Why Data Analytics and IoT Will Be Indispensable? Data analytics is an important part of the success of IoT investments or applications. IoT along with Data analytics will allow businesses to make efficient use of datasets. How? Let’s get into it! Impelling Revenue Using data analytics in IoT investments businesses will become able to gain insight into customer behavior. It will lead to the crafting offers and services accordingly. As a result, companies will see a hike in their profits and revenue. Volume The vast amount of data sets that are being used by IoT applications needs to be organized and analyzed to obtain patterns. It can easily be achieved by using IoT analytics software. Competitive Advantage In an era full of IoT devices and applications, the competition has also increased. You can gain a competitive advantage by hire developers that can help with the IoT analytics implementations. It will assist businesses in providing better services and stand out from the competition. Now the next question arises: Where is it being implemented? Companies like Amazon, Microsoft, Siemens, VMware, and Huawei are using IoT data analytics for product usage analysis, sensor data analysis, camera data analysis, improved equipment maintenance, and optimizing operations. The Rise of IoT Data Analytics With the help of IoT Data Analytics, companies are ready to achieve more information that can be used to improve their overall performance and revenue. Although it has not reached every corner of the market yet, it is still being used for making the workplace more efficient and safe. The ability to analyze and predict data in real-time is definitely a game-changer for companies that need all of their equipment to work efficiently all the time. It is continuously growing to provide insights that were never possible before.

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Straight to the Top: Why Incorta Beats Top Cloud Vendors in Dresner Advisory’s 2020 Market Study

Article | March 19, 2020

Business agility is the name of the game in 2020. Last year, the US-China trade wars gave business leaders around the world a preview of what it looks like when change and uncertainty become the new normal in the global economy—and for those caught flatfooted, it wasn’t pretty. Here we are nearly one year later and the world has changed dramatically once again. The trade war fiasco? That was just a dress rehearsal compared to what we are living through today with the recent outbreak of COVID-19. At times like these, few things matter more than having visibility into and the freedom to innovate with data to address the necessary business agility.

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Machine Learning vs. Deep Learning. Which Does Your Business Need?

Article | February 17, 2020

In recent years, artificial intelligence research and applications have accelerated at a rapid speed. Simply saying your organization will incorporate AI isn’t as specific as it once was. There are diverse implementation options for AI, Machine Learning, and Deep Learning, and within each of them, a series of different algorithms you can leverage to improve operations and establish a competitive edge. Algorithms are utilized across almost every industry. For example, to power the recommendation engines in all media platforms, the chatbots that support customer service efforts at scale, and the self-driving vehicles being tested by the world’s largest automotive and technology companies. Because of how diverse AI has become and the many ways in which it works with data, companies must carefully evaluate what will work best for them.

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AI and Predictive Analytics: Myth, Math, or Magic

Article | February 10, 2020

We are a species invested in predicting the future as if our lives depended on it. Indeed, good predictions of where wolves might lurk were once a matter of survival. Even as civilization made us physically safer, prediction has remained a mainstay of culture, from the haruspices of ancient Rome inspecting animal entrails to business analysts dissecting a wealth of transactions to foretell future sales. With these caveats in mind, I predict that in 2020 (and the decade ahead) we will struggle if we unquestioningly adopt artificial intelligence (AI) in predictive analytics, founded on an unjustified overconfidence in the almost mythical power of AI's mathematical foundations. This is another form of the disease of technochauvinism I discussed in a previous article.

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Spotlight

Zylotech

Zylotech is a Self-Learning customer data platform for marketers. Imagine having a 360-degree view of your customers on demand including their identity, behaviors and intent; Insight to non-obvious patterns of information only available through the latest AI models; Automation personalizing customer recommendations for you in the tool of your choice. This is the Zylotech advantage - bringing cognitive customer intelligence to your fingertips.

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