What do you mean by data analysis?
Data analysis refers to the process of collecting, organizing, interpreting, and extracting useful information from the raw facts and figures in the huge amounts of data generated by a business on a daily basis. The main responsibility of the data analyst is to translate burgeoning data into useful insights and then into insights, helping 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 enormous amount of data that flows into an organization’s databases has become a concern. Volumes have increased to millions and millions of gigabytes. Businesses have moved away from just directories, 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 also video, photos, sound recordings, and sensor data.
The transmission of data to an organization’s data warehouses is increasing at an exponential rate and is expected to grow to 50 zettabytes by 2020. One zettabyte is more than 931 million gigabytes! Each and every one of the actions we carry out online leaves a digital trail. Every action we take when we are online – like shopping online, chatting with friends through social media apps, or using GPS-equipped smartphones – generates data that companies mine for insights. Basically, we leave fingerprints with every action we take digitally that involves using the internet.
The amount of data generated is growing rapidly and this requires the use of advanced technology and tools specifically designed for the analysis and interpretation of this huge amount of data. This is where data analysis comes to the rescue. The complete 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 to handle Big Data.
Data analysis using these tools with mathematical and statistical algorithms will further help an organization to develop good decision-making processes and enable it to respond quickly to customer inquiries, resulting in increased willingness to the organization. High precision in Big Data analysis also ultimately helps organizations increase profits and reduce costs.
The development of new products based on current market trends can only be done when Big Data is analyzed with precision and precision. Customer satisfaction is very important if a business wants to be successful and popular with its target audience. Market trends and customer preferences need to be properly and specifically analyzed to develop products that are fashionable and acceptable to the target audience. The results of the data can even help companies take advantage of new revenue opportunities in the marketplace and ultimately improve customer satisfaction, thereby improving the operational efficiency and profitability of the company.
Just remember that data analysis is no longer an option or alternative. It has become the lifeblood of all businesses.
“DATA ANALYSIS IS THE LIFELINE OF ALL COMPANIES TODAY”.
