Can data be considered as the new gold? Considering the pace at which data is evolving all across the globe, definitely yes!
Let me show you some eye-opening facts and statistics.
Do you know that Netflix saves $1 billion per year on customer retention only by utilizing big data? Thats not all. 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! Theres more, among all the google searches. 15% of those are new and are never typed before, leading to a new set of data generated by Google 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 million 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 the list of 5 promising tips enterprises must acquire to turn their big data into a big success.
1. A Strong Leader for 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 converting their big data into a big success. Unfortunately, only 34% of the organizations have appointed a Chief Data Officer for the victorious implementation of big data initiatives. A pioneer in the utilization of big data in the United States’ 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.
2. Invest in Appropriate Skills Before Technology
Having the right technological skills is crucial, of which the following three are required:
- The capability of utilizing disparate open-source software for the integration and analysis of both structured and unstructured data.
- The capability of properly framing and asking appropriate business questions with a crystal-clean line of sight such as how the insights will be utilized.
- The capability of 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.
3. Perform Experimentation With Big Data Pilots
In the present age, numerous big data conversions emerge from technology vendors in case they have anything to do with the business case and return of investment (ROI) of big data. 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 big data laboratory 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.
4. Search For a Needle in an Unstructured Hay
The thing that always remains on the top of the mind of businesses is unstructured and semi-structured data. According to Gartner, data of organizations will grow by 800% in the upcoming five years and 80% of that data will be unstructured. Let us see 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 sentiment.
- Only analyzing the unstructured data is not enough. Extraction of relevant signals must be done from the insights and must be combined with structured data for boosting business predictions and insights.
5. Incorporate Operational Analytics Engines
One of the potential advantages 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 the high-value case under consideration, loyal customers who enter the promotional code at the time of checkout but discount is not applied, resulting in poor customer experience. Its 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. Making 20% of the organizations decisions with tech-powered analytical engines and then gradually increasing the percentage of decisions help organizations in developing a greater level of comfort.
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 at any cost the natural instincts of understanding patterns and deterring flows. Enterprises deal with different types of data each day. That 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 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.