4 Big Data Macro Trends You Should Definitely Watch

Just a few months ago big data was something nobody could really understand the gist of. Everybody made close guesses of huge data that is really tough to handle. Companies, professionals knew nothing much except for this is going to be something worthwhile in near future. That future isn’t any far now as the buzzword big data takes over the entire market. No more wild guesses and no more assumptions Big Data is probably the most used term when we come into the field of analytics. Big data analytics is again a term flipped way too high in the Information Technology market these days. For just a brief introduction, this article will let you know what exactly is big data and the four macro trends that are driving it insane.

Big data is pretty much a collection of huge data, that too raw data in what we call layman terms. Data these days is increasing at a speed hardly comparable from various sources. Not just millions of entries we need to deal with, big data is all about handling crore entries at once. Analyzing through the gaps, patterns and getting onto the real work is what is paid off high these days. Big data is too complex to get handled by the traditional processing ways. Artificial intelligence is thus the savior data scientists have probably work on. With the upcoming market initiatives, there are a couple of macro trends that have huge impacts on big data and the work driven by it.

1. Machine Learning & Artificial Intelligence

With just some training, computers can now respond better to your queries is a line that pretty much explains machine learning. Machine learning algorithms learn from huge databases of structured and unstructured data i.e. text, images, video or facial expressions. ML is basically a branch of AI that is concerned with the computers to learn without any sort of explicit programming. But often the two i.e. ML and AI are terms flipped together. With the increasing demands, machine learning has now gained an edge over all other techniques meant to deal with lump sum amounts of data. AI and ML together have even grown over cloud computing and blockchain technology. Enterprises are now investing huge on these two with a total estimate of $19.1 billion in 2018.

2. Data Governance

The increasing technological advances come down with a fear of governance too. How easy your access to data be, however efficient handling be, governance is the second most feared field after the first being skill set. With the recent Facebook and Cambridge Analytica Scandal, the fear of exposing the user’s or customer’s data has risen. No matter how much hard you try, there’s always a need to track your data. Where is it going, to whom is it going and how is it used, have to be the topmost answered questions by any organization.

3. Cloud Computing

Fast processing and easy accessibility of data is what an analyst requires. Cloud computing serves it all. Your data is already on the cloud, what you need is just the right tools to access and begin with the work. Public cloud vendors even provide you with some AI enabled or machine learning tools to further smoothen your work. The Teradata State of Analytics in the Cloud report has found even higher demand for cloud-based big data analytics. 83% of the surveyed companies said that the cloud is the best place to run analytics while 69% said they want to run all their analytics in the cloud by 2023. The very reason of this preference being: faster deployment, better performance, improved security, cheaper maintenance and easy access.

4. Need for Speed

Some organizations have now planned to reduce their focus onto compliance issues and rather invest in increasing the speed of analytics. Real-time streaming or some mission-critical applications are now some major areas big data is primarily used for. Such cases do require more of in-memory technology to enhance the speed at which work is done. Because obviously processing data in RAM is pretty much faster than having it accessible from the hard drive it is stored in. In some or the other way, the basic need for better speed is driving the other 3 factors big data trends on.

With the data-driven near future, all of the above-mentioned trends will significantly impact the organizations to use big data in a balanced manner that’s capable of intensifying the results.