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Business Intelligence (Generic)

BI 2

The business intelligence solution provides a framework that enables presentation of raw data from various systems into meaningful and useful reports that can be used to better run businesses.  It features a series of dashboards usually representing departments or functional groups within an organization. The dashboards allow the group to get on the same page with the latest information within the organization. This can include structured data like that present in ERPs or unstructured data like word or PDF documents. The business intelligence practice involves three areas of specialization: data extraction, data warehousing and presentation.

Key features of the solution include:

User Self Service: The dashboards are designed to enable business users to do as much as possible without the need for involving IT. The portal enables users to create and add new widgets, add new users or to slice and dice information into presentable reports based on a pre-defined data model.

Visualizations: Visualization is to data what a graph is to an equation. It helps represent the data graphically and makes discovery of patterns and trends easier. Examples of visualizations includes bar graphs,  line graphs, Pie charts, Surface Area charts, Scatter plots, Heat Maps, bubble, doughnut and radar plots.

Data from almost any source can be visualized using the solution. This includes most ERPs, Text, Excel, and other office files and any OLEDB/ODBC compliant data source. Most visualizations natively support representation of aggregated data like 'total sales by quarter'.

Predictive Analytics: The framework includes a comprehensive predictive analytics module that allows business users to interactively mine the data for trends that are not otherwise visible. The data mining engine supports several methods (algorithms) to discover patterns. These include

  • Classification: How are my sales $ related to the type of envelope we used for our marketing newsletter?
  • Regression: What will my sales be next month based on the previous 4 years of data?
  • Segmentation: What age groups buy my product the most?
  • Association: What products do customers buy together most often from my store? (market basket analysis)
  • Sequence Analysis: What pages on my website is the customer most likely to visit after the current page.

Big Data Analytics: Big data analytics is a new trend in the business intelligence community which enables processing of very large amounts of structured and unstructured data through parallel processing. Big data architecture reduces or eliminates the need to aggregate or pre-aggregate data in the form of pre-defined cubes. In scenarios where the query pattern is unpredictable and where real-time responses are critical, big data architecture is a clear necessity. Technology around big data is still developing and solutions are still implemented in specialized market segments. Our solution supports implementation through cloud variants of Hadoop and enables presentation of this information through the conventional presentation tools described above.

In memory: The analytics engine mentioned above supports in-memory analytical querying. The feature reduces / eliminates the need to store and query data through physical disks. All the data is stored in a machines memory (RAM) enabling extremely fast data retrieval. In certain cases, this completely eliminates the need to pre-aggregate data or to create pre-designed indexes on the datasets.

Cloud Collaboration: The dashboards are available in both on-premis and cloud variations. Other than the visualization, the solution also supports online database as a platform (PaaS/DaaS) solutions like Microsoft Azure and HD Insight.

Mobile BI: All reports on the dashboard are built using HTML 5. This enables rendering of all dashboards and reports on a variety of devices including most popular mobiles. We support Android, iPhone and Windows Mobiles by default.

Explore Other Examples

Explore how IT can help your business by


  • Enables Data based decisions
  • Responsible Organizations
  • Data availability where and when required
  • Customer insight
  • Cross/Up Sell
  • Streamline Operations
  • Improve Efficiency
  • Identify hidden business trends