Importance of Data Analytics

By 2020 every human being will create 1.5MB data per second on average and by 2025 the sum of digital data will add up to over 16 trillion gigabytes. So, it is an understatement to say that data is only big but in fact, data is huge. Thus, it is important to know about big data and data analytics.

Big data is a large volume of data that consists of structured and unstructured data forms and it helps organisations to draw meaningful insights from their data to learn and grow. So, it’s the data that matters and not it’s volume. Structured data is organised information that can be accessed with the help of simple search algorithms while unstructured data is less uniform and it’s difficult to work with as the lack of structure makes compiling data time and energy-consuming task.

The process of uncovering hidden patterns, unknown correlations, market trends, consumer preferences and other useful information from both structured and unstructured data is called Data Analytics. Analytics helps organisations make informed decisions and choices. It boosts the overall performance of the organisation by finding the financing processes, increasing visibility, providing insights and granting control over managerial processes. It detects frauds and flaws by keeping a close vigil. It further improves the IT economy by increasing agility and flexibility of systems.

Despite the growing demand for data analytics, there is a shortage of professionals with good data analytical skills. So, only 0.5% of the data we produce is analysed. A proficient data analyst must have certain skillset like computer science, data mining and business management with also good knowledge of statistics. Computer science skills include programming skills Eg: R, Python and technical skills Eg: Platforms like Tableau, Excel, Hadoop, Hive, Spark. The data skills include warehousing, quantitative, statistical skills, analytical and interpretation skills. Business skills are important to use data effectively and to improve various aspects such as operations, finance, productivity etc. These are the skills that make data analytics professional an invaluable asset for the organization. There are a variety of job roles across various organisations in this field like Data Analyst, Analytics Consultant, Business Analyst, Analytics Manager, Data Architect, Analytics Associate, Data scientist etc.

So, in summary, data analytics usage is augmenting at a great pace and is still to grow in future at a tremendous rate.

Pankit Gupta