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Five Tips To Convert Big Data into a Big Success

Can data be considered as the new gold? Considering the pace at which data is evolving all across the globe, there is little question. Consider the following: 

  • Netflix saves $1 billion per year on customer retention only by utilizing big data.
  • Being the highest shareholder of the search engines market, Google faces 1.2 trillion searches every year, with more than 40,000 search queries every second!
  • Additionally, 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 by Google continuously regularly. The main agenda is to convert data into information and then convert that information into insights. 

Organizations were storing tons of their data into their databases without knowing what to do with that data until big data analytics became a completely developed idea. Poor data quality can cost businesses from $9.7 billion to 14.2 million every year. Moreover, poor data quality can surely lead to wrong business strategies or poor decision-making. This also results in 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 a list of five things an enterprise must acquire in order to turn their big data into a big success:

Strong Leadership Driving Big Data Initiatives  

The most important factor for nurturing data-driven decision-making culture is proper leadership. Organizations must have well-defined leadership roles for big data analytics to boost the successful implementation of big data initiatives. Necessary stewardship is crucial for organizations for making big data analytics an integral part of regular business operations. 

Leadership-driven big data initiatives assist organizations in making their big data commercially viable. Unfortunately, only 34% of the organizations have appointed a chief data officer to handle the implementation of big data initiatives. A pioneer in the utilization of big data in the United States’s banking industry, Bank of America, specified a Chief Data Officer (CDO) 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. 

Invest in Appropriate Skills Before Technology

Having the right skills are crucial even before the technology has been implemented: 

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

All of the above-mentioned skills can be proactively developed for both hiring and training. It is essential to search for those senior leaders within the organization who not only believe in the power of big data but are also willing to take risks and perform experimentation. Such leaders play a vital role in driving swift acquisitions and the success of data applications. 

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 the identification of the problem, bring numerous aspects of big data into the laboratory where these pilots can be run before making any major investment in the technology.  Such pilot programs provide an enormous collection of big data tools and expertise that prove value effectively for the organization without making any hefty investments in IT costs or talent. By working with such pilots, implementation of these efforts at a grassroots level can be done with minimal investments in the technology. 

Search For a Needle in an Unstructured Hay 

The thing that always remains on the top of the mind of businesses is unstructured and semistructured data - information contained in documents, spreadsheets, and similar non-traditional data sources. According to Gartner, data of organizations will evolve by 800% in the upcoming five years and 80% of that data will be unstructured. There are three crucial principles associated with unstructured data. 

  • Having the appropriate technology is essential for storing and analyzing unstructured data. 
  • Prioritiing such unstructured data that is rich in information value and sentiments. 
  • Extracting relevant signals must be done from the insights and must be combined with structured data for boosting business predictions and insights.

Incorporate Operational Analytics Engines

 One potential advantage that can be attained by using big data is the capability of tailoring experiences to customers based on their most up-to-the-minute behavior. Businesses can no longer extract the data of last month, analyze that data offline for two months, and act upon the analysis three months later for making big data a competitive benefit.

Take, as an example, loyal customers who enter promotional codes at the time of checkout but discover that their discount is not applied resulting in a poor customer experience.

Businesses need to shift their mindset of traditional offline analytics to tech-powered analytic engines that empower businesses with real-time and near-time decision-making, acquiring a measured test and learn approach. This can be achieved by making 20% of the organization’s decisions with tech-powered analytical engines and then gradually increasing the percentage of decisions processed in this way over time as comfort grows about the process.. 

Final Thoughts 

In this tech-oriented world and digitally powered economy, big data analytics plays a vital role in the proper navigation of the market and to come up with appropriate predictions as well as decisions. Organizations must never ignore understanding patterns and deterring flows. especially as enterprises deal with different types of data each day, in different sizes, shapes, and forms. The market of big data analytics is growing dramatically, 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 as well as big data. Hence organizations must acquire appropriate measures and keep in mind all the crucial above-mentioned tips for turning their big data into big success to stay competitive in this ever-changing world.

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Comment by priye darshan on July 16, 2021 at 12:53am

5 Tips for Big Data to Big Success            

With all these challenges acting as a backlash against big data, we have compiled 5 tips for turning big data to big success that big data analytics companies must employ to maximize the value of big data -

1Big Data Analytics Companies must blend the Big Data Right at the Right Time

Most of the big data companies have wealth of big data right at their fingertips but they do not utilize it effectively. Turning big data into big success i s not without any challenges and thus organizations must prioritize their needs for gaining actionable insights. In most of the big data companies, it is not that data is not available; it is that data is not complete, organized, stored and blended right in a manner that it can be consumed directly for big data analysis.

2)Big Data Analytics Companies must define a definite Organizational Structure

Organizations with a dedicated predictive analytics business unit have a success rate 2.5 times better than those with ad-hoc or decentralized teams. Companies can make the most of big data analytics by have a centralized set-up for the analytics team. This will help them bring together business leaders and big data technology to intellectualise novel business use cases and outline best practices that other teams within the organizations can leverage.

3) Organizations must have a dedicated systematic and structured implementation

A big data survey found that 74% of the organizations do not have a well-defined criteria for selecting, identifying and qualifying big data business use cases. The survey found that 67% of the companies did not have well-defined key performance indicator initiatives to assess the big data initiatives.

4) A Strong Leader to Drive the Big Data Initiatives

Leadership is an important factor to nurture a data-driven decision making culture. For organizations to boast of successfully implemented  big data  initiatives, they must have well defined leadership roles for big data and analytics.

5)Finding the Right Big Data Talent

A recent CMO survey found that, only 3.4% of marketers believe that they have the right big data talent.

The war for finding the right big data talent is on, most companies feel that they are losing. Business leaders find it difficult to acquire the right analytical talent.

So how do companies find the right big data talent .

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