http://blog.maia-intelligence.com/2013/02/21/data-management-for-bi-2/

Posted on February 21st, 2013 by Vikram Kole

Data is the foundation for building reliable systems. Data Management for Business Intelligence covers a broad spectrum of services including Strategy & Architecture, Data Integration, Data Quality, Data Governance, Master Data Management, Data Warehousing and Business Intelligence & Analytics. The ability to exploit business data and extract the insights hidden within is predicted in the ability to transform raw data to timely insight.

Organizations face a number of common issues when it comes to both Data Management and Business Intelligence. Managing data is an essential but a difficult task as even miniscule inconsistencies can affect the success of the project.  Data is shared across organization and data ownership is not very clear. BI solution should be tied into organization’s overall strategic goals which is often not the case. Data Management practices must act as a catalyst, not an impediment, for business transformation.

Having an effective Data Management practice coupled with Business Intelligence can deliver on multiple fronts by driving results through better usage of data. This practice is effectively provides countless advantages, such as :

–   Creating actionable information driving improved decision making

–   Reducing operational costs

–   Monitor and improve organizational performance

–   Identifying profitability drivers and different revenue streams

–   Improved customer satisfaction with effective use of customer information such as CRM etc.

–   Improved Financial Planning & Analysis

On the other hand, not engaging in this practice brings huge risks. Managing data is imperative as even minimal redundancies, inconsistencies can result in unfavourable situations like :

–   Unclear information leading to ineffective decision making

–   Redundant data across organization leading to multiple versions of same data sets.

–   Inability to reduce costs

–   Less ROI, especially on IT

So how can we manage the ever growing data mountain for better results? There are certain practices which help in effective data management.

  1. Data Quality – Maintain the data quality by addressing data quality issues such as Data Collection, Formatting, Validity, Timeliness, Consistency etc.
  2. Data Integration – Review existing data architectures and data integration processes for redundancy
  3. Data Governance – Constantly evaluate the existing data processes for accuracy, control and authority of data mitigating the problem of inaccurate data.
  4. Master Data Management – Work with every business units and IT to help in planning and delivery of accurate information view across the organization.
  5. Data Strategy – Lead with a data strategy for various aspects including data architecture planning & implementation, data warehousing etc.
  6. BI, Reporting & Analytics Strategy – Identify data sources and design data modeling and BI system architecture with integrated reporting and analytics capabilities.

Providing the right information to the right people at the right time requires a lot more than a state-of-the-art fully functioning IT. Adequate focus is needed on improving data-gathering processes, adopting data quality standards and controls, and embracing user-friendly analytics is required. Today’s competitive environments demand the best use of enterprise wide available data which create several challenges. Yet the benefits and the opportunities it brings are significantly huge, not to forget the risks of not doing so are far greater.

Data Management for BI

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