Big Data Analytics refers to the procedure of gathering, organizing and examining large data sets called Big Data so as to uncover unseen patterns, unknown correlation, customer preferences, market trends and other important information. Basically, Big Data Analytics helps businesses make better-informed decisions by shining a light on data as well as by highlighting the important data in a large dataset.
What are the Challenges of Analyzing Big Data?
As a matter of fact, there are considerable challenges associated with Big Data analytics. The sources where organizations draw their data from, are varied and constitute both internal and external sources.
Additionally, the data comes in different formats, both structured and unstructured. In analyzing big data, an organization faces the challenge of breaking down data storages so as to get access to all data stored in various places. Creating platforms that can pull unstructured data as easily as they can the structured data also presents a unique kind of challenge.
The sheer amount of data collected by an organization in the modern era is too much and such challenges render conventional/traditional systems useless in analyzing. Big Data analytics, therefore, require sophisticated software as well as specialized tools and applications which can perform predictive analytics, text and data mining, data optimization as well as forecasting.
These processes, though separate, are highly integrated and help data scientists extract the knowledge from the data sets.
Some Benefits of Big Data Analytics
As much as there are challenges, Big Data Analytics can be very beneficial to organizations when used well. Information decoded from Big Data can help a company; uncover new revenue sources, better their customer service, improve customer retention, partake more effective marketing and have improved operational efficiency as well as give an edge over the competitors.
One other major benefit of Big Data analytics is that it enables data scientists and other data disseminating individuals to analyze forms of data; usually untapped by typical business intelligence (semi-structured and unstructured data types) in addition to analyzing structured data sets. This exposes the analysts to wider knowledge and patterns that can’t be uncovered by conventional analytics programs.
What is the Usage of Big Data Analytics in these modern times?
Currently, with advancement in technology, the application of Big Data Analytics is practically limitless. With the quick and precise dissemination of huge data chunks, analysts can make high-level decisions such as decoding DNA within moments as well as security analysis such as decoding terrorist plans.
Furthermore, Big Data analytics can be used in the business industry for example in determining the kind of adverts consumers are most likely to respond to.
The telecommunication industry is one other industry that heavily relies on Big Data analytics. Many mobile carrier companies rely on Big Data analytics in a bid to understand the huge information from customer calls, texts and emails.