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Master Data Index

Data Management Solutions For Enterprise

Master data management (MDM) provides a trusted view of master entities to help achieve customer centric objectives and business results. Without a clearly defined master data, the enterprise runs the risk of having multiple copies of data that are inconsistent with one another. Since there are disparate systems within the organization, providing a single source of truth is difficult. In case of merger/acquisition, each of the organizations will have its own master data and how to merge the two sets of data will be challenging .

ElogicSquare

Data Challenges

  • Operations suffer from inconsistent, incorrect, and slow data
  • Redundant analysis and repeated data reconciliation due to lack of reliable information repository.
  • Lack of sharing and comparing across the system results in lost opportunities.
  • System upgrades require too many resources and cannot simply be done enterprise-wide.

Some of the services offered by ElogicSquare in this space are:

  • Master Data Management (MDM)
  • Master Data Governance (MDG)
  • Data Quality and Data Integration
  • Data Migration

Why Master Data Management & Governance? (MDM/MDG)

  • Master Data is the core reference data that describes fundamental dimensions of business and supports all transactions and analytics/reporting.
  • ElogicSquare delivers the governance processes needed to build and maintain a centralized source of data for accurate intelligence.
  • The drivers of data governance are usually regulatory and legal requirements; however a governance rule can be any practice to which the organization wishes to adhere.
  • Governance often dictates where certain types of data may be stored and codifies data protection methods, such as encryption or password strength.
  • Governance can dictate how to back up data, who has access to data, and when archived data should be destroyed. Organizations can also set governance objectives around improving data quality or breaking down silos that isolate certain data.

The end result of all this, from a Product Information Management perspective, is to be able to:

  • Provide higher quality data; prevent mistakes and bad decisions
  • Enforce standards across thousands of product categories and many systems & processes
  • Increase productivity – IT does not have to write laborious programmatic rules for product data cleansing
  • Accelerates time to market and reduce costs for new product development
  • Facilitate product-related compliance with government regulations (pharma, life sciences, etc.)

Company’s First flagship product in this space, LogiMDI, represents the next generation of master data index (MDI) and consumer master data management (MDM) technologies. It is a software-as-a-service (SaaS) solution that is powered by customer matching technology. LogiMDI is the most accurate, easiest to implement, most secure, and most cost-effective MDI on the market.

LogiMDI: The challenges faced by Master Data Index (abbreviate MDI) during the match and link process are magnified due to organization -specific standards with regards to data quality, completeness, metadata coding, other governance aspects, but also between systems within the same organization.

We at ElogicSquare have built a Master Data Index solution , LogiMDI on our Multi-Tenant Platform. The algorithm is a hybrid model built based on probabilistic and fuzzy matching heuristics, resolving patient identities across systems and organizations leads to:

Access to patient's complete medical history

  • Improved quality of care
  • Lowers operational cost
  • Lowers the probability of repeat tests and treatment delays
  • Indentifying Duplicates

LogiMDI uses probabilistic algorithms to match patient records. The algorithm assigns a rank to different data elements based on a preset acceptable level of certainty and scores the likelihood that two or more records belong to the same patient. The higher the score, the higher the probability that there is a match between two records

The challenges faced by MPI (abbreviate MPI) during the match and link process are magnified due to organization -specific standards with regards to data quality, completeness, metadata coding, other governance aspects, but also between systems within the same organization.

We at ElogicSquare have built a Master Patient Index solution on our Multi-Tenant Platform. The algorithm is a hybrid model built based on probabilistic and fuzzy matching heuristics, resolving patient identities across systems and organizations leads to:

  • Access to patient's complete medical history
  • Improved quality of care
  • Lowers operational cost
  • Lowers the probability of repeat tests and treatment delays