5 Characteristics of Big Data
Big data has become one of the biggest and most recognizable terms in commerce in recent years. In truth, the term big data is self-explanatory. Big data is simply large amounts of data, and while there is nothing new about the concept of big data, the things we can do with it now are cutting edge.
Even though there is no true definition for big data, there are some characteristics that you should expect from big data technology. Continue reading to learn more about the features of big data analytics and how your company can benefit from a big data strategy.
1. Big data is big.
As the name indicates, one of the main characteristics of big data is that it’s big—in fact, it’s ginormous. To get an idea of who “big” big data truly is, with capable big data technology, you can manage petabytes of data. Petabytes are equal to 1,024 terabytes.
As you can imagine, the larger the volume of data your company has to work with, the easier it is to pinpoint areas of the market that are ripe for the taking and identify ways to make your operations more efficient. Through data mining, big data technology can analyze data from large databases and provide different types of analytics from predictive to streaming.
As one of the industry leaders in big data technology, Tibco actively seeks to increase what we’re able to do through data analytics. In fact, one of their main goals is to equip the data scientists of the future with the big data analytics software they need to continue making our technology smarter and more customized.
2. Big data is fast.
Another one of the most important big data characteristics is velocity. Businesses, governments, and NGOs need big data in real-time, making velocity a critical feature. The quicker you can get insights into markets and operations, the quicker you can make adjustments and crucial decisions.
You can credit the velocity of big data to the use of machine learning algorithms that employ artificial intelligence to collect and clean terabytes of information as soon as it’s available. Big data increases the speed with which insurance companies make policy decisions and played a monumental role in the velocity of the global COVID-19 response. So you can see why big data is big business.
3. Big data is accurate.
When gathering a large amount of data from various data sources, including the internet of things (IoT) and relational databases like social media, it’s paramount to ensure the veracity of such a huge amount of data. One of the best features of big data is that it’s much more accurate than traditional data means and methods.
The old ways of collecting and analyzing data were too prone to human error. When you’ve got data from different data sets such as data lakes and data warehouses, veracity is of the utmost importance and integral to data quality.
4. Big data promotes variety.
Another great characteristic of big data is that you can collect, manipulate, and analyze a variety of data from multiple data sets. From mobile devices to various social media platforms, you can collect all types of data and use it to optimize your business operations and products. Data mining technology enables you to compile large amounts of data and recognize variables that enable different types of analytics like predictive analytics and visualization.
5. Big data is time and cost-efficient.
The traditional methods of managing a large volume of data aren’t only outdated, but they’re also costly and time-consuming. Big data processes make intricate data easier and cheaper to collect, store, and manipulate. The time and money spared by big data business processes mean that execs can designate data stewards within the company to watch over and manage data rather than enduring the IT specialist hiring process.
While there is no real definition for big data, it’s revolutionized the way we collect and apply business intelligence. With the ability to store and manipulate large volumes of data and different types of data from different sources in real-time, big data analytics is the wave of right now and the future.