2019 is drawing to a close, and you know what that means. It’s time for technology predictions for 2020. And there are plenty of those to go around. If you search for them on Google and look at the summaries, you’ll notice that almost all of them mention AI and robotics. You can’t read an article about 2020 without seeing one or the other or both.
So, to make things interesting, this article is bucking the trend and focusing on other technology, leaving AI and the robots to Gartner and Forbes (except for one small exception at the end). So, without further ado, here are our top 5 predictions for 2020.
GPUs (graphics processing units) have been driving advances in games and professional graphics for more than decade. But lately, data scientists and IT departments have discovered that GPUs are good for a lot more than a realistic fight in Super Smash Brothers. GPUs are now providing computing power for big data analytics. An example is using massive amounts of images of malignant and benign tumors to train models to show when a tumor needs investigating.
The latest development in this space are GPU databases that are more flexible in processing many different types of data, or much larger amounts of data. Because big data and real-time analytics are needed now more than ever to deliver customer experiences that drive competitive advantage, GPU databases will be a hot item in 2020.
MDBS is the abbreviation of multi-database system, sometimes also called a multi-model database system. Companies today can have different models of databases, often residing in different business units and storing different kinds of data and transactions. Accessing data from those databases outside the business units has been tricky at best. Resolving the issue has usually required moving the data somewhere else using ETL (extract, transform, load) processes that are time-consuming and compute intensive.
MDBSs offer access to the data stored in these various individual, separate databases. They can query data using different models including relational, NoSQL, and more. As the number of cloud databases and NoSQL databases mingling with relational databases increases in 2020, MDBSs will be just what the doctor ordered to enable access to the different data models.
Hybrid cars. Hybrid mattresses. Hybrid clouds. Hybrid fireplaces. The world is full of hybrids—including hybrid IT. Hybrid IT is a mixture of on-premises data centers, private clouds, and public clouds. For years, hybrid has been organic. Enterprises have added to cloud to their IT, but most still have on-premises systems, too. After cloud proved to be a successful infrastructure for Amazon, Google, and other digital companies, the push from analysts was to move everything to the cloud as soon as possible. However, for most companies, that is not practical, cost-effective, or secure.
So, as this decade of the cloud is coming to an end, enterprises have realized that hybrid IT doesn’t have to be organic. It can be a conscious choice. For example, banks can keep confidential customer account numbers and personal identifiers safely in a database on a mainframe while delivering a mobile experience to the customer from the cloud. So, 2020 will be the year that you’ll see companies devising thoughtful hybrid IT strategies that assign the proper computing tasks to the proper infrastructure.
Now that IoT devices are used in everything from cardiology clinics to your thermostat, edge computing has appeared on the scene. Edge computing enables the analysis of data from IoT devices before it’s sent to a data service or cloud. Edge computing can process and store data faster than the cloud, which allows for more efficient real-time applications, such as running facial recognition on a smartphone or edge server or gateway instead of a cloud-based service.
Edge computing is fast, secure, reliable, and scalable. It significantly reduces latency and costs. With the advent of 5G and its superfast network speeds, edge computing will make a major impact in 2020. From video conferencing to monitoring agricultural machinery on remote farms, edge computing use cases will be everywhere by the end of next year.
The evolution of the chatbot is our one tiny nod to AI and, by extension, robotics. We’ve all gotten used to them on websites. Their friendly little robot faces or avatars with human names greet us when we land on a page and ask if they can help us. They answer basic questions like “How can I view my account?” or “Where can I find pricing?” If our questions are more complex, they offer to connect us to a “human in customer service.”
However, thanks to Siri and Alexa, chatbots are on the verge of becoming “a virtual assistant in customer service.” Advances in sentiment analysis, the improved ability of voice recognition to detect emotions from tone of voice, and technology that makes robotic voices sound human are bringing us Chatbot 2.0 (or, if you prefer, Chatbot 2020). By this time next year, you won’t be typing a response or question to a bot with a name like “Jiff” on many of the web or mobile sites you visit. Instead, you’ll be able ask Jiff a question out loud, and Jiff will answer back. Think how much faster things will be when you don’t have to type all the time.
No matter how sophisticated and futuristic technology gets, there’s still one thing it will always need—the data and infrastructure to make it happen. So, if you happen to read any predictions that declare “the relational database is dead,” “middleware will be gone by 2030,” or “no one will be using mainframes in 2025,” ignore them. GPUs, MDBSs, hybrid IT, edge computing, and VR assistants are all powered by databases, optimized through re-platforming applications (many of which are on the mainframe), or connected by middleware---or any combination the three. There’s always a place for the old with the new.
If you’re interested in learning more about what TmaxSoft has to offer in 2020, we’d like to hear from you. Just visit tmaxsoft.com and start a conversation with our friendly chatbot.
Raghu Radhakrishnan is the CEO & Managing Director of TmaxSoft India. With more than 27 years of sales and marketing experience in the IT industry, he drives global enterprises to adopt TmaxSoft technologies and help them solve their perennial problem of high cost of ownership. He joined TmaxSoft in 2015 and has held senior level positions with IBM, Modi Olivetti and Digital. He holds a degree in Mechanical Engineering from PSG College of Technology, Coimbatore, India.