Do you get significant business value from Data?  Is your Enterprise Data well managed?

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Data is a double-edged sword; some organizations are very good at deriving values from it while others experience accessibility, quality, compliance, privacy and security issues.

You derive value from data, this means that you know which business challenges you are trying to solve (opening new channels, reducing fraud, improving product quality, reducing waste, etc.). Then you explore how data will help you solve the issue.

As for managing data well, it means you know the answers to these questions:

  • Where is the data located?
  • Can I access it easily? / Can I protect it?
  • Are only the right persons allowed to access it? / Who is responsible for it?
  • Can I trust it? / Which version is the truth? / Is it consistent with other sources?
  • Can I explain the provenance of data?
  • Do we keep data long enough according to regulations?
  • Do we discard data according to regulations?
  • Can we handle the volume? / Can we handle the speed?
  • Do we have the right skills to manage the data lifecycle?
  • Do we know which data is consumed by processes and/or applications?
  • Do we have a corporate glossary?
  • Do we know the business rules associated with the data

Enterprise Data Governance / Management Consulting

Our expertise covers entire spectrum of EDG/EDM: AI, BI, Data Governance / Quality / Lineage, MDM, Big Data & Analytics, Data Architecture / Security / Privacy, Metadata and Operational DB.

Data is fragmented in organizations and integrating it is harder than most people think… Here are some of the practices, architecture, processes and tools you should consider deploying to take care of this critical asset:

  • Data Architecture & Governance (including SIPOC and CRUD matrices)
  • Master Data Management (MDM)
  • Data Quality with stewardship/ownership/custodianship
  • Business Glossary
  • Data Dictionary (including mapping)
  • Service Based Architecture
  • Metadata Management & Data Lineage
  • Governed Lake House
  • Data Privacy
  • Retention and Archiving (ILCM)
  • BI and Advanced Analytics
  • Security including Risk and Threat Analysis
  • Security in the cloud
  • Data Policies

As you can see data manifest itself in many ways. We contributed to the design of enterprise-wide data models for multiple organizations. To these models, we added user defined functions in various data modeling tools (ErWin, Powerdesigner and more) to integrate data governance elements such as ownership, custodianship, and stewardship as well as retention policies. We used six sigma SIPOC to associate data to business processes and we built CRUD matrices in organizations using Information Engineering principles. We were involved in MDM projects and implemented operational processes to handle data quality.

We reused the ITA&S-F metamodel to hold all these relationships in some projects, we also helped organizations to built their own metamodel supporting their EA framework with same purpose of capturing all these relationships. Recently, we helped in designing a governed Lake House with multiple security measures for a large organization.

Finally tooling got better, tools like Purview, Collibra and more end-up supporting these relationships.

Some of our team members worked in organizations where data privacy was paramount and got a great understanding of privacy and security. And as you must have noticed at this point, we are quite experienced in BI, Big Data & Analytics. In short, EGM/EDM requires multiple expertise than can only be acquired through many years in projects involving data from all these angles.

We are familiar with metadata layer technology, from AtScale and new ones like Denodo and Dremio to create a semantic layer directly on the Data Lake or for Data Fabrics situation or both.

Finally, we also offer a 'rent a CDO (Chief Data Officer)' service to put in place such a function, replace a departure or help bring up to speed an executive in this role.