Data Quality Management Services
Organizations require consistently reliable and trustworthy data to realize maximum value from their data. Without high-quality and accurate data, your organization cannot understand and act upon your most imporant metrics. With a Data Quality Management solution in place, key individuals on your team will know the exact state your business is in at any given time, what your customers are saying, and be able to take action when it matters most. When you lack solid Data Quality Management processes and tools, Data Quality issues can quickly arise from:
- Training and data entry issues
- Poor business processes
- Poor Data Interface and Data Integration design
- Poor Master Data Management
- Lack of understanding of data sources
Poor Data Quality Management can expose a company to many risks such as:
- Poor business strategies, financial decisions and management decisions driven by poor Data Quality
- Inability to identify new business opportunities
- Inability to collect revenue in a timely manner
- Negative impacts to business reputation due to poor customer service
- Exposure to regulatory and compliance sanctions
Data Quality Solutions
Effective Data Quality Solutions can be overwhelming because they must be governed throughout the organization and over the entire data lifecycle. In addition to the processes and tools for ensuring high Data Quality, mechanisms must also be in place to monitor, measure and report the level of Data Quality across the organization.
The concepts behind Data Quality Solutions are not new, however many organizations have failed to put the appropriate solutions in place. With today's technological advances, many companies find themselves overwhelmed with the massive amounts of data available to them. Often the cross-functional cooperation needed to ensure data quality proves a daunting tasks, as does the discipline required to follow set rules and procedures.
Meridian’s Data Governance Team can assist you with assessing the many dimensions of Data Quality within your organization to ensure that your data is accurate, complete, timely and consistent.
Data Quality Tools
What are Data Quality Tools and why are they important? In recent years the market for these technology tools has become increasingly relevant and visible as more organizations are realizing the impact poor-quality data can have on their goals. Traditionally, Data Quality Tools have been designed to align with CRM-related activities such as data cleansing and deduplication efforts. However today's tools have expanded beyond these initial capabilities and are driven toward a holistic view of data management from beginning to end. Several areas are addressed, such as:
- Data Gathering: From disparate CRMs, spreadsheets, and other databases, many organizations are often surprised in all the places their data is held. The first step in any process is to understand exactly what you're working with.
- Data Cleansing: Once the data is gathered, it is then reviewed for consistency. Often various departnemtns, people, or tools enter data in different formats. The cleansing process modifies the data values to meet organizational standards. Formatting values into consistent data sets is critical at this phase.
- Cross-Referencing & Matching: Duplication is inevitable. All data values need to be cross-referenced across all data sets. Decisions will then be made for matching values with duplicates often being removed or merged.
- Data Profiling: Data often has meaning beyond the face value of a particular entry. Analyzing data can capture insightful statistics into the original quality as well as help pinpoint data quality issues.
- Solutions Monitoring: Once the data gets to this stage, and the proper Data Quality Tools are put into place, the solution is monitored for continued performance and organization adherance.
- Ongoing Enrichment: To ensure continued data quality the value of internally held data can be appended with related attribute sets from external sources.
Our Storage footprint and cost was continually increasing, Quality of test data was insufficient in spite of higher volumes of accounts to provide more scenarios, refreshing test environments was time consuming due to higher account volumes, no method in place to provide purge functionality that would maintain data integrity. After implementing the Meridian EDMS platform the Immediate result was the elimination of 17TB of premium storage that supported test environments and one high end Unix server that hosted the databases, reductions in storage growth provided O&M savings of $2 M costs over 5 Years, avoided capital costs of $4.4 M from storage purchases no longer required, smaller test databases through EDMS functionality that provides representative samples of accounts specific to our installation, faster test database refreshes through EDMS representative samples and Improved test quality through an EDMS data extraction process which allows users to extract accounts that specifically address their test scenarios.
— (BGE) Baltimore Gas and Electric Company