Why data is so important for the business 

The use of analytics is no longer limited to big companies with deep pockets. It’s now widespread, with 59% of enterprises using analytics in some capacity. According to a survey from Deloitte, 49% of respondents say that analytics helps them make better decisions, 16% say that it better enables key strategic initiatives, and 10% say it helps them improve relationships with both customers and business partners. But in order to take full advantage, you need to know how to get the most value from your data.

The world’s most valuable resource is no longer oil, but data.

- The economıst

Companies need to translate data into information to plan for future business strategies. For most companies, valuable data is stored in massive spreadsheets or servers. Ideally, this data should provide you with information on sales trends, consumer behaviour and resources allocation. Company data can indicate the viability of your product and help in the planning of your future growth. Hence data can help maximize revenues and reduce costs.

How data analytics can help your business

Analyzing data more often than not increases efficiency, but also helps identify new business opportunities that may have been otherwise overlooked, such as untapped customer segments. In doing so, the potential for growth and profitability becomes endless and more intelligence-based.

Through data analysis, business operators can get a clearer view of what they are doing efficiently and inefficiently within their organizations. When a problem is identified, professionals those supported by analytics tools are capable of answering crucial questions such as:

  • What was the cause of the problem? (Report)
  • Why did it happen? (Analysis, Insight)
  • What will happen in the future? (Prediction)

Why Datametric?

Because Datametric is a data-centric company. With 10+ years of experience in Business Intelligence (BI) and Data Analytics, Datametric will accurately identify business needs and become your guide in the data age.