By Rachel Lee - October 11, 2021
Big data analytics is the practice of processing high volumes of data (think terabytes and petabytes) which businesses use to reveal insights, patterns, and actionable decisions. Such data comes from multiple sources and can be structured or unstructured.
What makes data “big”? There’s data, and then there’s big data. Today’s businesses rely on the power of big data to get ahead in today’s fast-moving world. But they also need some truly advanced analytics and data science to understand and make the best use of large datasets.
That’s where big data analytics tools come in. Big data technologies like communications service providers (CSPs), diagnostic tools, and financial analytics are built to tackle the high volumes and varieties of data, and the velocities with which big data sets get populated.
Let’s dive deeper into the advantages offered by big data analytics over smaller-scale traditional data analytics.
More than just a large amount of data, big data encompasses data sets with a scope beyond that of traditional relational databases. Data scientists tend to think of big data in these terms:
Besides handling high volume and variety of data, big data analysis also requires the ability to process data quality, considering aspects such as:
Today, most data analysts deal in five types of big data analytics, which include:
Working in the present, prescriptive analytics recommends the best actions to take for a situation as it is unfolding.
Using techniques like data mining, drilling down, and correlation, diagnostic analytics helps data scientists understand why something happened in the past, such as identifying consumer and market trends.
Similar to diagnostic analytics in its focus on the past, descriptive analytics cover what happened in the past.
Predictive data visualizations and other types of predictive analytics forecast what’s most likely to happen in the future, using modeling, data mining, and machine learning to do so.
A rising specialty within data analytics, cyber analytics use a data-driven approach to protect against cyber attacks.
Businesses can benefit greatly from such enhanced data processing:
In our globally connected world, incomprehensible volumes of new data are generated every second. That means businesses have to be able to not just process new information, but also be ready to make new decisions and prepare to shift gears faster too.
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See just how much you can save in costs, time, and energy for yourself by scheduling a demo with Sisu’s Decision Intelligence Engine today.