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Democratization of Big data
Throughout the COVID-19 pandemic of the past two years, the value placed on quality data has exploded. The argument could be made that in today’s environment—that is, one riddled with economic turmoil, record-high inflation, and talks of a looming recession in the aftermath of a global pandemic—data is in greater demand than ever before.
An organization’s ability to democratize its data and transform it into valuable insights is a crucial function with a value that cannot be overstated.
Data-backed decision-making has a measurable positive impact on organizations, as a recent survey of C-suite executives from around the globe discovered that: “Companies that excel at integrating data into their strategy, operations and culture are largely outpacing their peers in revenue growth and profitability.”
At the same time, we have entered the era of “stakeholder capitalism,” with many companies acknowledging that success is contingent on their ability to serve all stakeholders—including employees, customers, suppliers, the environment, communities and, of course, shareholders.
Against this backdrop, top leaders are recognizing that as data becomes their most important resource, trust must become their most important value
What is Big Data
Think of a collection of data sets that are so large or complex (comprising: images, texts, audio, and videos) and cannot be analyzed by traditional databases or tools such as spreadsheets. That is exactly what big data is.
The amount of data generated by the internet is so large. Matter of fact, there are about 2.5 quintillion bytes of data created each day by internet users worldwide. Statistics revealed that the size of global data is expected to grow at a compound annual growth rate (CAGR) of 13.2% to about $274.3 billion by the end of 2022.
According to big data growth statistics, in 2019 the market was forecasted to grow by 20%. In 2012 and 2013, the growth rate of big data was as high as 61% and 60% respectively. This growth is expected to continue to increase because of the increase in internet usage. According to Forbes, the number of registered internet users in 2014 was approximately 3 billion and by 2019 this figure had increased to reach 4.1billion. Thus there had been an unprecedented increase in global data.
Big Data is actively applicable across all spectrums of life and further digitization
Ecommerce
Data analytics and big data help businesses understand and map consumer buying patterns, trends and needs. Through this E-commerce providers, vendors and digital marketplaces can better serve better stakeholders and offer better services.
Marketing
Big Data analytics helps to drive high ROI marketing campaigns, which result in improved, lead generation and sales. Through data analytics and mining of data on content consumption marketers can better map and track consumer interests screen time to better generate demand and qualify leads for business needs.
Education
Big data help researchers and Policymakers track the trends in education and draw insights on how to improve, target and influence state-building through education and learning. Adequate data generation and analysis will help provide better education and financing options for students
Healthcare
Data analytics is useful for delivering quality healthcare delivery, research and tracking of disease cycles unique to different countries and demographics to keep ahead of a health crisis like the COVID-19 pandemic. This was used by the Pioneering 54Gene in talking and tracking covid cases in Africa.
How has big data impacted the Financial Industry?
The financial industry is one of the top investors in big data according to IDC Semiannual Big Data and Analytics Spending Guide. The amount of data generated by the financial industry is huge. And the ability to put that data to use in making business decisions and effectively process it to obtain insight is very critical to staying competitive.
Through the improvement of data analysis, Banks easily can monitor credit patterns and scores. It also helps to monitor or flag atypical activities and anomalies that may signal fraudulent transactions or money laundering.
Data gathering and analysis of customer banking and spending habits through a Bank’s services will provide more accurate insights into the needs activities and the quality of the bank customer to determine what further services the customer will need.