You can no longer ignore data analysis

What do you mean by Data Analytics?

Data Analytics refers to the process of gathering, organizing, interpreting and extracting the useful insights from the raw facts and figures of the huge amounts of data generated by a business on a daily basis. The main responsibility of data analysts is to translate the growing data into useful perceptions and then into valuable information and help organizations make smart decisions based on data rather than relying on instincts.

How important is data analysis?

In today’s world, the accumulation and storage of the huge amount of data flow to an organization’s databases has become a problem. The volumes have increased to millions and millions of gigabytes. Companies have moved far from only folders, data sheets and documents.

But at the end of the day, it is almost impossible to analyze and interpret all this data. This data includes not only text, but videos, photos, audio recordings and sensor data.

The data flow to an organization’s data warehouses is increasing exponentially and is expected to grow by up to 50 zettabytes by 2020. A zettabyte is over 931 million gigabytes! Every single action we perform online leaves a digital trail. Every single action we take when we go online, such as online shopping, chatting with friends through social media applications, or using GPS-equipped smartphones, generates data that companies leverage for information. We basically leave digital footprints with every action we perform digitally involving the use of the internet.

The amount of data generated is growing rapidly and this requires the use of advanced technology and tools specifically designed for analyzing and interpreting this huge amount of data. This is where data analysis saves. The in-depth and in-depth analysis of this “Big Data” requires the use of data analysis software such as Python, SAS, R and Hadoop, which were developed specifically for handling Big Data.

Data analysis using these tools with mathematical and statistical algorithms will further help an organization develop good decision making processes and allow it to quickly answer customer questions, resulting in an increase in goodwill for the organization. The high accuracy of Big Data analytics also ultimately helps organizations increase profits and lower costs.

Developing new products based on current market trends can only be accomplished when Big Data is accurately and accurately analyzed. Customer satisfaction matters a lot if a company wants to be successful and popular with its target audience. Market trends and customer preferences must be analyzed correctly and specifically to develop products that are trendy and acceptable to the target audience. The data findings can even help companies take advantage of new market revenue opportunities and ultimately improve customer satisfaction, thereby improving the company’s operational efficiency and profitability.

Just remember that data analysis is no longer an option or an alternative. It has become the lifeblood of every business.