Orbit Blog

ORBIT Analytics  |   August 8, 2017

The term Business Intelligence has been around since the 1920s, but gained prominence from the 1950s onwards. The advent of data processing mainframe systems and early DBMS allowed for data to be stored, processed and reported. Interest in BI revolutionized in the 1980s with relational database systems, spreadsheets and even more in the mid 1990s with data warehousing and OLAP systems. Today’s advances in big data storage, cloud and faster processing have made business intelligence an integral part of a company’s IT setup.

The traditional Business Intelligence with the data warehouse platform used ETL (Extract, Transform, Load) to deliver aggregated reports. These ETL platforms continue to exist in organizations. However, they may not be able to respond to the changing business’s needs. The rapid transform and analysis of data is more important than ever to meet the new business user’s needs. The resulting trends, prescriptions and predictions need to be agile, user-friendly and trusted.  This has caused organizations to buy market products with built in analytics which are readily accessible for the business user.business intelligence interest graph

For an organization planning to revamp or buy a new business intelligence platform, there are many options. The BI professional must pick the right system to meet the needs of the users and the lines of businesses they are supporting. 

  • Financial business users need a robust reporting platform that can be built on an operational data store (ODS).
  • Sales and Marketing users need real-time trends to build their campaigns.
  • HR users need employee profile data analytics to manage their workforce plans.
  • Management needs competitive intelligence

 Each of these can be met by specialized BI solutions that focuses on Descriptive Analytics. The traditional approach to meet these needs would be to build a BI platform that extracts, models, transforms, analyses and delivers the insights. The modern BI platform directly taps into data sources to extract and provide ready available content for the business users to manipulate and analyze. The insights tools use data visualization and storytelling to provide actionable insights.

 The specialization of BI solutions is not restricted to the lines of business. There are multiple product lines at every stage – Data modeling, Ingestion and Storage, Analysis, Data visualization. Many of these solutions are self-service, especially on the visualization space, thereby removing the barriers of on-going investment in BI professionals. The evolution of transforming data into actionable intelligence will continue to evolve with advances in technologies most notably in IoT, Machine learning and Blockchain.

ORBIT Analytics, a cutting edge software for Reporting and Business Intelligence, is designed as a self-service solution enabling users with data-discovery reporting and descriptive analytics. Understanding the data that you have today is the first step of the Business Intelligence staircase, followed by more of the advanced predictive and statistical analysis. ORBIT Analytics has simplified taking the first step into the Business Intelligence space and continues to help organizations to work towards a data driven ecosystem. Contact us today to learn more about how we can make your business “intelligent.”

About the Guest Blogger

Atma Shetty is a product specialist bridging the gap between business needs and technology solutions. His expertise lies in conceptualizing, designing, building and implementing enterprise products at large companies. Over the last 19 years, Atma has built and implemented products in areas of finance, securities, order to cash, retail, supply chain and telecom. He has been a programmer, technical lead, business analyst, project manager and product manager.  He has been recognized by peers and clients for his expertise in using practical technology solutions. Atma is currently implementing innovative solutions at a major healthcare provider in Seattle, Washington.

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