Why This Approach ?

Data Quality is the sum of all the parts of your Data Strategy and Data Architecture efforts.

Drive Data Quality

You know you have failed to some degree if your data consumers cannot perform their job function (or processes) due to bad data. Therefore this must be fixed.

Data Quality has three (3) perennial characteristics, that in effect can drive all data investments:

  1. Data Consumers (not Data Producers) determine if the data (service or product) is fit for purpose and will call out if the Data Quality is acceptable.
  2. Listening to Data Consumers (internal or external) in micro-detail is paramount to measuring the efficacy of your Data Architecture, Data Governance and Data Strategy efforts. (We have taken this concept of capturing Data Consumer feedback to a new scientific, scalable and algorithmic level).
  3. In it’s purest form, Data Quality (the value, accuracy, relevance, timeliness, meaning, lineage and presentation) to deliver the right data to the right person/process at the right time, is what will drive every data thought, every data investment and every data improvement made by data leaders.

Sadly, these concepts get missed in the noise of cloud, mobile, big data and analytics conversations, and generally lie at heart of most data initiative failures.

Drive Data Maturity

The ambiguous piece (most often missed and generally poorly understood) of all of this is the $-dollar-value / concrete-commercial-metrics that can be discovered, and drive investment good data quality, and in turn, justifies the inclusion of a full and robust Data Maturity Landscape, with all that entails (Metadata Management, Master Data Management, Reporting & Analytics, Data Governance, Data Quality, and so on).

The full circle as we see it looks like this:

  1. Understand the $ value of Data Quality (and when data is NOT working for data consumers
  2. Use the metrics and evidence to drive fundamental improvements and $ investments in Data Maturity
  3. Return to 1 and remeasure (loop)

Drive Data Strategy & Execution

with Data Consumers and the heart of our thinking, we have discovered an approach that is now a proven, automated, multi-year process, with commercial case studies and metrics to show organizational gains and business performance improvements.

Resulting in Happy Data Consumers

As clever as ClearDQ is, it is not just a powerful software bot & app. It sits deep in a proven Data Maturity lifecycle, and drives a healthy Data/Information delivery programme for any organisation resulting in happy Data Consumers !

Data Quality for Financial Performance