In our increasingly complex digital society, we generate a tremendous amount of data. With data being an important element in the modern business landscape, its use is no longer limited to big companies with massive capital. Nearly 59% of enterprises are using data and big data analytics in some capacity. Today, big data is the buzzword around, as with the amount of data being produced every minute by consumers and businesses worldwide, there are potential values to be found in big data analytics. As more and more organisations depend on data, the demand for data professionals constantly rises, and the demand for big data analytics courses is further in-demand.
If you seek to become a data professional, you must know about big data analytics and its importance. Keep reading this article as we intend to familiarise you with the same.
What is Big Data Analytics?
Big data analytics is collecting, examining, and analysing data to discover market trends, patterns, and insights that are valuable for companies to make better decisions based on the insights from the data. Moreover, information is available quickly for businesses to be agile in building plans to maintain their competitive advantage.
Big data analytics uses advanced analytics on the large collection of structured and unstructured data to produce valuable business insights that can lead to business growth and productivity. It is widely used across an array of industries, namely insurance, artificial intelligence, education, healthcare, and manufacturing, to understand the need to improve systems, profitability, and processes.
There are four types of big data analytics for supporting and informing business decisions. The four types of big data analytics are:
- Diagnostics Analytics
- Prescriptive Analytics
- Predictive Analytics
- Descriptive Analytics
Big data analytics require tools to analyse data. Thankfully, technology has advanced, and there are many intuitive software systems that data analysts can use to conduct big data analytics. Some of the popular big data analytics tools are:
- NoSQL databases
- Distributed storage
- Predictive analytics Hardware Software
- Stream analytics tools
- Data mining tools
Why is big data analytics important?
In the contemporary technologically-driven world, big data analytics is fueling our online activities in nearly all industries. Big data analytics is important for the modern business landscape because of three broad reasons,
- It offers a better understanding of customers and competitors
- It can drastically increase the conversion rate
- Big data analytics is efficient in improving customer engagement and experience
Big data analytics has now become integral as it helps companies leverage their data to identify potential opportunities for improvement and optimisation. It also helps organisations reduce costs and build better customer-centric products and services. Most importantly, big data analytics increases overall efficiency across different business segments, resulting in higher profits,intelligent operations, and satisfying customers.
The big data analytics market is booming globally, making it the most sought-after career path. If your next step is to opt for a professional course, then pursuing a big data analytics course can make you employment ready across many fast-growing sectors.