Origin of Cohelion: The action of process of multiple independent parts to become aligned around a central theme. Used in Astronomy and in Information Theory

Data Quality

Easily review, clean and adjust your company

Before all your integrated data moves to your Enterprise Data Warehouse you want to guarantee the data quality. Ultimately, this data is being used to feed your BI and analytic tools in order to make the right business decisions. The data which is being transferred to your Enterprise Data Warehouse is often a black box for many organizations. The Cohelion Data Platform offers a unique process and a user-friendly interface where you can inspect, clean and adjust all data. Now you are in full control because all of your data is in one place, with all users using one source to access their data.

All relevant data in one accessible platform

The Cohelion Data Platform allows you to quickly see and review all of your relevant data whether it’s HR, Finance or Operational data, consolidated from all your sources. For instance, your account managers can see their clients (current, historical and also forecasted) data. Region managers can see the performance of their offices and so forth.

Integrated and automated data quality checks

Both the process of importing data as well as the captured data itself is closely monitored. Deviations from expected data refresh cycles are notified, as are failed imports. Our anomaly detection algorithms are triggered by data that deviates from certain benchmarks. Plus unknown product codes or customer codes are flagged to be mapped in MDM. All these checks are designed so your business users are in full control without the need to involve your IT staff.

Data workflows

Involving your users in the data-validation checks will have a huge positive impact on overall data-quality of your Data warehouse. Via pre-defined workflows your users will be invited (and reminded) for data-entry, corrections and approvals. This can be set up via regular automated processes tied to monthly historical data reviews, forecasting processes or annual budgeting rounds.

Include data from inaccessible applications

Often smaller department or niche-legacy apps are not worth connecting (yet). However, its data still is essential for the total picture. In these cases the platform provides various ways to include this data as well, either via data entry via a web form, or by uploading excel spreadsheets. This unique feature also allows you to start your data warehouse project early even when your infrastructure is not ready for it. The platform is designed for growth and allows for seamless transitions to other automated data sources, even if multiple sources deliver the same data at the same time.

Detect incorrect data and adjust

There are always cases where data is incorrect in your source system and cannot be corrected. Instead of getting back to your IT staff to modify complex ETL scripts, we offer you the possibility to review and correct data before it’s submitted to your Data Warehouse. We believe that ‘garbage-in is garbage-out’ should not be an excuse.

Extensive audit trail and full lineage

The platform keeps an extensive audit trail of all modifications, corrections and manually entered data. A full history of all previous values is stored and can be checked by authorized employees within your organization. Since full data lineage is maintained, your consolidated statistics can be broken down at any time. This gives insight into the data origin and gives the ability to trace errors back to the root cause.

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