Less of Data, More of Intelligence

 In Enterprise Services

Data is pouring in huge volume and in different formats but to make it dependable, processing needs to be done on it. In other words, raw data needs to be converted into relevant information. This can be done by processing the data in a way that it delivers relevant insights into business operations. As per research conducted by Forrester, processed data (i.e. information) contributes to all functional areas of an organization, contributing majorly, 73%, to Competitive Intelligence and 71% to Cost Management.

The need of the hour is to realize the importance of data and unlock its potential to back up company’s support system. According to a recent research, business agility is dependent majorly on business intelligence. This brings us to extend enterprise applications to merge with scalable concepts including data analytics, reporting, data warehousing, data mining and business intelligence.

Mingling analytics and data processing yields data which can then be used to formulate strategies, target markets in a better way and allocate resources most optimally.

This is how Diaspark can help you stay ahead. We provide state-of-the-art excellence to sort out meticulous data and empower decision makers to stay informed and take better decisions. With a comprehensive package of data services that begins from Reporting and Analytics, we provide the valued information in the form of Big Data.

Drilling down to the benefits of specific data services that Diaspark caters to its clients, they are as follows:

Data Reporting

  • Visual dashboards for quick operations & understanding
  • Predictive Analytics for enhanced performance
  • Higher transparency by increased trust among customers

Data Warehousing

  • Robust data architecture
  • Increased data quality and consistency
  • Historic data intelligence

Business Intelligence

  • Data- after the fact v/s Predictive Analytics
  • Faster and better decision making
  • Automated Processes with reduced labor costs

Big Data

  • Data Accuracy
  • Predictive risk analysis
  • Improved dialogue with customers
  • Reduced maintenance costs

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