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Turn Big Data into a Big Success: 5 Tips for Effective Big Data Analyticsby@alihatanveer
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Turn Big Data into a Big Success: 5 Tips for Effective Big Data Analytics

by Aliha TanveerJuly 12th, 2021
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The market of big data analytics is tremendously progressing and will reach up to $62.10 billion by the year 2025. Netflix saves $1 billion per year on customer retention only by utilizing big data. Bad data can cost businesses from $9.7 billion to 14.2 million every year. Only 34% of the organizations have appointed a chief data officer for big data initiatives. To deter this problem, here is the list of 5 promising tips enterprises must acquire to turn their big data into a big success.

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Is data the new gold?

Considering the pace at which data is being used across the globe, definitely yes!

Let's see some crazy stats. 

Do you know that Netflix saves $1 billion per year on customer retention only by utilizing big data? Or that Google gets 1.2 trillion searches every year, with more than 40,000 search queries every second! There’s more, among all the google searches. 15% of those are new and are never typed before, leading to the fact that a new set of data is generated continuously.

Organizations were storing tons of their data into their databases without knowing what to do with it before big data analytics.

Bad data can cost businesses from $9.7 billion to 14.2 million every year. Moreover, poor data insights can lead to wrong business strategies, poor decision-making, low productivity, and sabotages the relationship between customers and the organization, causing the organization to lose its reputation in the market.  

To deter this problem, here is the list of 5 promising tips enterprises must acquire to turn their big data into a big success. 

Invest in Leadership  

The most important factor for nurturing data-driven decision-making culture is leadership. Organizations must have well-defined leadership roles for big data analytics to boost the successful implementation of big data initiatives.

Unfortunately, only 34% of the organizations have appointed a chief data officer for big data initiatives.

A pioneer in the utilization of big data in the United States’s banking industry, Bank of America, have specified a Chief Data Officer who is responsible for all the data management standards and policies, simplification of It tools and infrastructures that are required for the implementation, and setting up the big data platform of the bank. 

Skill Development

Invest in the following three skills:

  • Utilizing disparate open-source software for the integration and analysis of both structured and unstructured data. 
  • The capability of framing and asking appropriate business questions with a crystal-clean line of sight, such as how the insights will be utilized. 
  • Knowledge of statistical tools for performing predictive analytics and generating forward-looking insights. 

Perform Experimentation With Big Data Pilots

Start with the identification of the most critical problems of the business and how big data serves as the solution to that problem. After identifying the problem, experiment on numerous aspects of big data where these pilots can be run before making any major investment in the technology. 

Big data labs provide an enormous collection of big data tools and expertise that permits organizations to run a pilot and prove value effectively without making any hefty investments in IT and talent. Implementation of these efforts at a grassroots level can be done with minimal investments in the technology. 

Focus on the Unstructured Data 

According to Gartner, organizations' data will evolve immensely in the upcoming five years, and 80% of that data will be unstructured. Let us lay our eyes on the three most crucial principles associated with unstructured data. 

Assurance of having the appropriate technology is essential for storing and analyzing unstructured data. 

Prioritization and attention to such unstructured data are important that can be linked back to the individual. Also, it is imperative to prioritize such unstructured data that is rich in information value and sentiments. 

Incorporate Operational Analytics Engines

One of the most potential advantages can be attained by using big data tailoring experiences to customers based on their behavior.

It’s high time for businesses to shift their mindset of traditional offline analytics to tech-powered analytic engines that empower businesses with real-time and near-time decision-making. Companies must acquire a measured test and learn approach.

Final Thoughts 

Enterprises deal with different types of data each day. The data exists in different sizes, shapes, and forms. The market of big data analytics is tremendously progressing and will reach up to $62.10 billion by the year 2025. Considering that progression, 97.2% of the organizations are already investing in artificial intelligence and big data analytics. Hence organizations must acquire appropriate measures for turning their big data into a big success.