Vision

What does the future hold…

Big Data is an area that has had a lot of attention but many people find it hard to define. A common definition is the three Vs which is data that has Volume, Velocity, and Veracity. It is important to understand that Big Data does not have to be all three. For example Big Data does not mean just high volumes of data. If an organization has data that users need quickly and it comes from many different sources or is a variety of types then it is often still Big Data. As thought leaders, we at D3 see Big Data continuing to grow and be needed. NoSQL options will continue to gain adoption and D3 can guide you to success. As more organizations need to process Video or Images and graphics, then graph databases and other NoSQL technologies will become better options. Databases like Neo4J will continue to gain adoption as well.

Mobile data continues to make huge gains in adoption. It is important that users have access to their data and are able to access it on their terms. While users need consistent access, there are also many other uses for mobile and small devices. As IoT devices get more use, they also get smaller. IoT devices must be very small and also produce a lot of useful data. The devices themselves must communicate back to the users for analysis and must be able to run analytics right on the device. Small devices like Raspberry Pi will become more important to both users and IT alike. Mobile devices are both on the data creation and the consumption side. We at D3 see these devices to become even smaller with more power and D3 continues to guide customers so they can maximize the use of the devices.

AI is another area that continues to advance. Machine Learning is a great example of AI and organizations are beginning to have important uses for AI. As analyzing video and other non-text data sources, machine learning is very important. Neural Networks are how Machine Learning applications are trained and then the machines can pick out and predict various outcomes. Big Data and Machine Learning together make for an important pair. The larger the volume of data, the better the machine can be trained. TensorFlow is an open source set of libraries for Machine Learning started by Google. The TensorFlow libraries help developers to create applications that then users can use the results to better understand their own data. D3 helps guide clients to better outcomes with Machine Learning and helps organizations become more competitive and improve results.