How good is the health of your data?
Many organizations cannot answer this seemingly basic question. Most lack objective facts regarding the health of their data to provide a good response. In fact, even when poor data quality is suspected as the culprit behind suboptimal business performance, few firms know what to look for in order to pinpoint the problem and prescribe corrective action.

Why is the health of data so important?
Widespread agreement exists today that poor data quality exposes companies to an array of business risks: financial, market, operational and legal. Therefore, a critical component to managing an organization's exposure is determining the accuracy, completeness and consistency of mission cricial data that feeds into every business decision. Without high quality, reliable data even the most seasoned businesses can fall victim to suboptimal decision making and non-compliance of regulatory requirements.

Why do you need help assessing your data?
Assessing one's health requires skill, experience and test equipment. Assessing the organization's data is no different than going to a doctor for an annual health check. Trained Content Engineers know what they are looking for, detect symptoms of trouble, and conduct additional testing before they recommend corrective action. Accomplishing this task is no small feat. Most internal resources are typically not equipped or trained in dealing with this level of complexity in data analysis.

At Utopia we bring years of industry experience working with master data – it's our core competency. We are in the business of offering strategic solutions through intensive data management. We have developed a unique methodology to uncover data issues, prescribe pinpoint solutions, and deploy tools and resources to quickly transform data thereby improving the health, vitality and most importantly the reliability of enterprise data.

What is the Data Health Check Methodology?
The Utopia Data Health Check is a process conducted to objectively assess the quality and characteristics of any data source. It is the logical first step to establish overall health (the what and where) before any data transformation can take place. In doing so we not only uncover what needs fixing today, but also establish processes to keep your data clean on an ongoing basis.

  While it can be conducted any time, changes to systems, new implementations or
   corporate events such as M&A are typical trigger points

  Carried out on a representative sample of data to determine the quality and
   characteristics of an organization's data

  Conducted by Content Engineers who also have domain expertise in the related
   industry

  Requires comprehensive testing, analysis and comparison with standards

  Findings are delivered on easy to follow drill-down views

  Report concludes with recommendations on data transformation and potential
   process improvements

The Process
The entire process takes less than two weeks, beginning with an understanding of the history behind current data formats, business rules, and finishing up with a detailed report of our findings and recommendations.

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Our Approach
Our Content Engineers focus on four key areas:

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