As a technology company, Altair is always anticipating trends and industry movements. Constantly moving forward, we set our goals to improve the way business is done for our customers. Data analytics solutions give companies the tools to make smarter, more calculated decisions to enhance their business. As we start 2020, there are three emerging trends that I believe will impact the industry.

AI and Analytics Teams Merge

The foundation of how data analytics teams are organized will change as artificial intelligence (AI) and analytics teams begin to merge into one discipline. Statistical model building and computer science has essentially combined into one. As a result, data, analytics, and machine learning (ML) teams will have to collaborate to better derive value from the same data. Additionally, more companies will look at initiatives to democratize data by granting the right people access to data pertinent to them, so it can be used to make optimal decisions.

Commercial AI and ML Tool Usage Will Increase

The vast majority of AI and ML projects are done using open source platforms. Open sourced tools are used to create innovation in the algorithms used in model building and deployment environments. Many commercial vendors initially provided limited connection to the open source eco-system, but this is rapidly changing. Commercial packages address the enterprise needs of an analytics environment – including collaboration, data lineage, model management, and integration with other tools and applications.

IoT Data Utilization will Grow  

Used with other traditional data sources (unstructured text, database, etc.), reliance on IoT data will increase in many analytic endeavors. This data provides insight for product design, product use, and can predict potential product failure. For example, it could be used to influence post-sales customer touch points and future marketing or loyalty campaigns. Data analytics will help deliver on better customer experiences and place users above their competition.

At its foundation, data analytics is a very technical discipline. For businesses seeking to implement new competitive strategies, wishing to reduce risk, or looking to solve any complex business problems, successful data analytics requires more people to use and understand the technology. The information must be shared quickly, to drive decisions on the discovered insight. Not doing so will let the competition move ahead.

Our teams here at Altair are equipped to help our customers manage the inevitable increase in the use of data analytics for decision making. We’ve designed our self-service data automation and machine learning tools so that more people with varying levels of experience can collaborate as data is accessed, transformed, and analyzed. Whether the need is to more efficiently reuse scripts made from open source tools, analyze voluminous amounts of new data that is generated from almost all electronic devices, or scale data analytics without compromising team-based collaboration and governance, Altair can help.
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