The 4 Types of Data Analytics Every Modern Company needs
Every company is sitting on a gold mine that is their data. Data has turned today's market into a data-driven business landscape wherein business owners and companies can't go with whatever they prefer to or follow their gut feelings or whims without basis.
To succeed in today's market, conglomerates and corporations invest heavily in research and development. They prioritize making sound decisions for growth, efficiency, innovation, and profit maximization.
In this scenario, sound judgment is the insights that data analytics is able to harvest from a company and a market's raw data. Data analytics allow the use of business intelligence and other tools to create forecasts, reports and optimization suggestions that companies can use as the blueprint of their business decisions.
Types of data analytics in business
Considered as one of the fundamentals when it comes to data analytics, descriptive analysis sets the foundation for understanding and summarizing raw data. It is mainly just analyzing existing data sets to provide a clear picture of what has happened in the past. Descriptive analysis techniques include data visualization, summary statistics, and data profiling. By employing descriptive analysis in your company, you stand to gain a comprehensive overview of your operations and performance in all aspects. The results garnered from using descriptive analytics can then be used to apply other analytic techniques to create projections for your company's future.
Usually done alongside prescriptive analytics, predictive analytics uses the past data of your company to create forecasts that predict future outcomes and trends. It uses algorithms, statistical modeling and data mining to create customer and market-centric projections such as predicting customer behavior, company performance and market stability. The projections created can then be used by your company to change and develop current processes to be ready for the predicted future trends. Predictive analytics catalyzes a company's awareness phase so they can begin planning how to stay ahead and adapt to changing market conditions.
Prescriptive analytics takes predictive analysis a step further by creating data-driven recommendations so that companies can proactively optimize outcomes. It combines historical data and predictive analytics with optimization algorithms and statistical models to create actionable insights – which your company can then follow. These actionable insights help companies answer questions like "What should we do?" and "How can we achieve the best outcome?" And gives them the chance to know what exactly to change and develop to achieve efficiency and maximum profitability.
Text and Sentiment Analytics
Have you heard of natural language processing (NLP)? NLP is the ability of machine technology to understand human language. In text and sentient analytics, NLP is used on market data such as customer demographics and buyer trends to understand consumer sentiment, identify emerging trends and assure customer satisfaction. By applying text and sentiment analytics to customer data, your company can increase customer satisfaction, brand loyalty and marketing efforts to retain existing customers and tap into new markets – effectively increasing the revenue of your company.
Data Analytics as a science is broad, with several types of data analytics for different kinds of data and situations. By focusing on the types of data analytics used in business settings, you can effectively leverage data analytics into a tool that will help your company stay on the map regardless of changing market conditions. Tapping into data analytics may just be your key to your company's security and longevity!
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