Data analytics technology is an aid for businesses to be more cohesive, efficient and informative than before. Businesses will be able to take useful actions when the quality of the collected data is reviewed and the analysis is thorough, precise and accurate. Read our previous blog on Data Analysis for an introduction to the topic.
A data life cycle mainly involves around collecting, curating, storing, using, sharing, archiving, and destroying data. All versions of the data lifecycle will contain some version of the six activities. Business needs drive forward the data needed.
Data provides consistent insights to finance professionals. These timely insights lead to better and faster adaptability and predictions. Collecting data does not make a finance organisation data-driven. It requires investment in tools and personnel. Data-driven enterprises have three key characteristics:
- The right data needs to go to right person at the right time
- Business units must be able to derive insights from their data
- Business units need to work and share their data and insights with each other
What should finance enterprises do to embed analytics in its processes?
- Make analytics an integral part of everyday decisions
- Make analytics part of every business process
- Analytics can make connections and reveal patterns in business activity
Companies that have successfully applied data analytics
A typical organisation will have a variety of analysts and engineers that fall into the following categories of data engineers, business analysts, data scientists, statisticians, accountants, financial analysts and data visualization specialists.
Data analytics technology is being used in different organisations to gain a competitive edge and improve agility. This technology plays a pivotal role in boosting many sectors like Banking, Healthcare, Retail, and Insurance. Some of the key company examples are stated below.
Amazon is the biggest e-commerce example of successful application of data analytics. It uses technology and customer data effectively. The data collected relates to customer visits, time spent on the site, customer names, email ids, addresses, payments and search history. Amazon then uses this information for a faster, more efficient customer experience and indirectly to optimise sales based on past purchases.
2. Capital One:
Capital One Financial Corporation, an American bank, uses data analytics for effective marketing. Demographic analysis and customer spending analysis is used for more targeted and significant marketing. This leads to better conversion rates of potential customers.
- General Electric
General Electric, an American multinational conglomerate, uses data to improve working methods, reliability and efficiency. By GE’s estimates, data can boost productivity in the U.S. by 1.5%, which over a 20-year period could save enough cash to raise average national incomes by as much as 30%.
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