Hello Everyone,

Data is the life-blood of any business.  It can be used to understand employee behavior, customer interactions, market fluctuations, etc., and it can alter the way business decisions are made.  Your business not only needs reliable access to the right types of data, you need that data to be clean, free of duplicates and mistakes, and available for complex analysis.  Astir IT specializes in business intelligence and Big Data and would like to present you with a case study of how we helped a client optimize their data environment.

As always, if you are interested in learning more about how we have addressed a specific topic that you do not see here or on our website (www.astirit.com), please contact us to discuss further.

We had a customer who had a data problem.  Data on customers, employees, competitors, etc. was all collected using different methods and housed in different places.  The customer lacked the expertise and tools necessary to combine, clean, and analyze the data in any meaningful way, and their strategic business decisions were suffering from it.  The customer came to Astir IT needing the creation and maintenance of operational dashboards.

After working closely with the customer, there were four (4) main operational areas that were affected by this lack of actionable data: HR, Finance, Accounts Payable/Receivable, and Operations.  Astir tackled the initial business analysis task, and helped the customer fully flush out the requirements:

• Human Resources Analytics: Identifying headcount trends, attrition rates, employee demographics, etc. in order to provide insight into trends concerning hiring, terminations, and retention.
• Finance Analytics: Advanced analytics in the area of bookings-to-revenue lifecycle; giving the client an accurate representation of the ordering process, backlogs, reserves, and billings in order to make inferences and trending projections for upcoming quarters.
• Invoice Analytics: Invoicing specific analytics designed to flush out information throughout the invoicing lifecycle; such as policy violations, expenditures, supplier lists, etc.
• Forecasting: Inference based analytics measuring planning, financial forecasting, expense data, cost center levels, account expenses, etc.

Once the business intelligence metrics were fully defined, a dashboard solution was implemented that initially combined, standardized, cleansed, and deduped existing data in order to populate a series of multi-tier dashboards.  In order to maintain these dashboards and ensure the customers ongoing ability to make use of the dashboards, a set of proper procedures were designed and implemented to collect and transmit data into a single repository, which was mined by the dashboards.  The customer was presented with a reliable and secure methodology to consistently measure and understand the right data in order to improve their strategic business decisions.

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