The sheer amount of data available has exploded, much more than any single company can handle. As a result, how a company consumes data is more significant determinant of success than how much data they collect. Let’s explore the importance of data consumption and see the resources businesses can use to optimally process and leverage their data.

Why data consumption is important

Raw data is unusable, while processed data is key to driving business decisions.

  • Data consumption is the process of transforming raw data into processed information readable by business intelligence (BI) software, which then extracts meaningful analyses and patterns
  • A company’s approach to data consumption can be critical to finding actionable information for increasing sales, improving customer experience and retention, reducing operating costs and capturing a larger market share

The future is data analysis

The digital economy has evolved beyond the point where data collection alone can facilitate success.

  • Getting ahead requires collecting and evaluating data to gather crucial insights on market demand, running lean, and generating consistent returns
  • In the 2020s, we have concrete methods, tools, and resources to streamline both processes
  • It’s time to equip your business to achieve exponential growth by prioritizing strategic data consumption

Methods of data consumption

Descriptive Analytics evaluates historical data to identify patterns and trends

  • Diagnostic Analytics reviews data to determine why an event occurred in the past
  • Predictive Analytics analyzes data to forecast or predict future patterns
  • Prescriptive analytics applies descriptive and predictive data to test multiple variables and calculate the best possible outcome
  • When processing data, there is no one-size-fits-all method

Tools that drive data analysis

Third-party analytics

  • Google and Facebook
  • Internal data analysts
  • Custom-built data platforms
  • Integrating technology to streamline and automate your processes
  • A model approach for a commercial real-estate operator to select the best resources to analyze their data

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