The driving force that is enhancing businesses today is big data analytics. It has become the key to instant market research and critical decision-making. The more data your enterprise can collect on its external and internal activity, the better chance you have at weeding out operational waste and increasing productivity.
How Big Data Analytics Is Reshaping Business
Everything that happens online can be transformed into data that can be analyzed. The same is true of what goes on in the physical world if the activity is captured by a digital device, such as a camera or a sensor. Analyzing measurements in processes, such as the consumer purchasing experience, can help you identify system vulnerabilities and apply solutions much faster than the conventional way of fixing things long after they are broken.
By studying big data, you can learn answers quickly to questions about your operations involving, for instance, stability, revenue, and employee productivity. This data can be seamlessly accessed from a management portal that gives you easy ways to monitor various company activities. Essentially, this analysis allows you to see patterns to help you arrive at decisions for refining operations, products, and services.
The Types of Big Data Analytics
- Descriptive analytics obtains a summary of historical data that's easy to read. It's useful for analyzing a company's revenue, sales, and other financial data.
- Diagnostic analytics helps identify and solve problems, such as technical glitches.
- Predictive analytics uses historical and current data to make predictions.
- Prescriptive analytics provides a solution based on programmed input.
Learning from Big Data Analytics Lifecycles
Here are the eight stages for analyzing big data and how it improves your operation:
Stage 1 - Business case analysis: a business case encompasses reasons for data analysis.
Stage 2 - Data identification: various types of sources that generate data are identified.
Stage 3 - Data filtering: corrupt data is removed.
Stage 4 - Data extraction: data is transformed into a compatible format for the tool, while incompatible data is extracted.
Stage 5 - Data integration: data is integrated if it occupies the same fields across different datasets.
Stage 6 - Data analysis: analytical and statistical tools are used to mine for relevant information.
Stage 7 - Data visualization: analysts can use visualization tools to generate graphics to help simplify analysis.
Stage 8 - Final result: a comprehensive report is generated for stakeholders to review.
Why Big Data Matters
The key to making big data work for your company is to utilize data in a way that helps you speed up productivity, while reducing or eliminating elements that cause barriers to success. The more effectively your firm uses big data, the greater your chance of seeing growth.
Strategic data analysis can help you achieve the following:
- Savings on expenses - cloud-based cost saving apps can help you identify areas of your business in which you can cut costs.
- Better knowledge of market dynamics - analyzing customer purchasing behavior and attitudes can help you understand your target market better.
- Insights on your online reputation - marketing tools, like Cision and Meltwater, can help you research what people are saying about your company online, which can help you identify customer needs or pain points.
- Improve customer growth and retention - as customers are the most important assets of a business, big data tools can be valuable at identifying what works and doesn't work for generating new leads and getting repeat business.