Why Big Data needs to become Smart Data? | 7wData

Why Big Data needs to become Smart Data? | 7wData

Businesses have always sought the perfect tools to improve their processes and optimize their assets. The need to maximize company efficiency and profitability has led the world to leverage data as a powerful tool. Data is reusable, everywhere, replicable, easily transferable, and has exponential benefits for the business. It can provide useful business insights on customer lifecycle, anomaly or issue detection, real-Time data analysis, etc. However, even if data could be a fantastic tool, it is limited if you can extract and interpret the knowledge from the information.

The question now relies on how to process, understand data, and infer useful insights more efficiently and acceleratedly.

This article looks into Big Data and how it develops into Smart Data. Additionally, we will look into the concept of Smart Data and its benefits for businesses.

Five main characteristics often describe Big Data:volume, value, veracity, velocity, and variety, aka the five V’s. Many experts also consider an additional one: variability. All these attributes compose what we know as “Big Data.” Each of them is key for understanding and analysis of the data.

This concept is not new for companies, as they collect a great volume of information that increases daily. As I understand it, we collect and analyze large amounts of data to obtain actionable insights businesses use to enhance their processes. This is why Big Data is so important for any industry sector.

Did you know that it is estimated that the volume of data generated worldwide will exceed 180 zettabytes in 2025? According to Seagate’s report, that same year, 6 billion consumers, or 75% of the world population, will interact every day with data, and each connected person will have at least one data interaction every 18 seconds. In other words, the volume and the velocity of information will force businesses to increase their data processing speed. Consequently, over the next few years, Big Data will continue to be a key support for strategic development, decision making, enhanced streamlining operation/ business operations, and customer relationships.

Nevertheless, the volume, value, veracity, velocity, and variety of information will force companies to focus on adapting and starting to use tools that help them process the data quicker and smarter. This is where the concept of “Smart Data” emerges.

Smart Data tools help pre-process the data when ingested to reduce the time of the analysis.What makes “smart data” smart is that the data collection points are intelligent enough to understand the data immediately.Not all data provides the same value to companies; in this scenario, the quality of the information will prevail over the amount of stored data. For example, it allows a device sensor to output useful human-readable data before sending it to a database for storage and/or detailed analysis.

Consequently, Smart Data analytics is the natural evolution of Big Data that aims to treat volumes of data intelligently, as it allows companies to obtain, among others, the following key benefits:

The volume of information that companies ingest doesn’t have any value raw. It needs to be cleaned and then curated to extract any knowledge. By implementing smart software, the data stream or batch will already come partially curated, which could be extremely important when there is a time restriction. For example, a self-driving car can’t afford to wait for data to be sent to the cloud, analyzed, and sent it back.

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