Big Data Trends in 2020

There are a lot of Big Data trends to prep for in 2020. As time goes on, it is important to take note of the new trends, as these trends can be used to help either grow or get more business, in the new year. We all have accepted the fact that Big Data and advanced analytics are valuable, it has become the modern staple for many industries such as from retail to manufacturing. It is estimated that the rise in total data content around the world is equal to 44 zettabytes of data, or 44 trillion gigabytes.

What’s more interesting, however, are the trends formed as a result of the newer digitally-reliant solutions. They specifically help shape the industry, altering how business analysts work with data. What will our digital future look like? How will we manage all this information? What skills should business analysts be focused on developing?

Specialization of Jobs

For a while, data analyst and scientist roles have been universal and there was never an urge to find someone specialized in one field or another. However, with the rise in Big Data and analytics, companies have now started focusing on individuals with specific knowledge of the type of data they are dealing with. Everything from manufacturing to financial services and logistics is being upgraded to rely more on digital services and as a result an influx of real-time data. There are plenty of opportunities but the key thing to remember is to choose one and become specialized in it.

Machine Learning Experience is a Must

By 2020, more than 40% of all data science tasks will be automated thanks to machine learning technology. Due to its exponential growth in capability, machine learning is able to extract insights from data at a much faster rate which would otherwise be too difficult for even the most skilled analyst. An increased speed not only improves efficiency for an organization but it allows for faster reactions to certain events. Quantitative analysis, experimental analysis, data scaling, automation tools and, of course, general machine learning are all skills that modern data analysts should seek to hone.

The Rise of Regulation

With the trend of Big Data and analytics becoming widely used across different industries, regulations are being set into place which is going to have monumental impacts on data processing and handling, consumer profiling, and data security. Businesses are under intense pressure not only to comply with the requirements established but also to understand the impact on current and future operations. Data scientists that are skilled in both data security and privacy are going to be in high demand. As more regulations come to be, that demand will continue to grow making it a viable specialization for current and future professionals.

Stay on the Bleeding Edge

Staying at the top of the latest trends and changes in technology is going to be the key indicator of success for many analysts and individuals in this business. Yes, technology is changing at a rapid pace and sometimes it can be difficult to stay on top of it, but what is worse is relying on a skill that will eventually become obsolete and then having to start everything from the beginning.

With databases, for example, choices may include NoSQL, HBase, and MongoDB but its likely priorities may shift over time. For frameworks and languages, there’s SAS, Python, R, Apache Hadoop and many others. The popular tools, on the other hand, include Power BI, ETL, IBM Db2, and Teradata. The important thing to remember is that these are popular right now, but these will eventually change over time and being able to adapt to new changes fast and effectively is going to determine your level of success.

Cloud Computing and Related Mechanics

As the demand for more elastic and fluid infrastructure grows, analysts and scientists will need to understand how this relates to current operations and equipment. Without cloud computing, none of these technologies such as Big Data, advanced analytics or machine learning would exist. Currently, the focus is based on tools and processes that would help achieve a greater understanding of data stores. However, as technology progresses, the focus is going to shift towards the underpinning hardware. Hence, the overlap between software and hardware related roles and the need for future professionals to understand the full scope of the systems at play.

Basic Business Intelligence Experience is a Must

Scientists are required to interact with teams and individuals from different areas of an organization to collectively find a solution to a problem. Similarly, data professionals mich be able to communicate effectively with others and be able to explain complex concepts in a simple way to non-technical professionals. Communication happens to be a critical soft skill of business intelligence. Along with programming skills, communication and leadership skills are going to be vital for analysts to be successful in their jobs.

In conclusion, data analysts are going to continue to grow as they take on more projects and build experience in the industry. But fostering the right growth, into specific areas and skills, can help professionals achieve success. It is up to analysts to not only understand the different tools that are used today but to also keep up to date about the new tools being introduced into the industry if they plan on staying relevant with technological changes. More importantly, professionals should seek to specialize in various industries to boost their value and skillset.