Services > Enable > Data Quality

It all hinges on data quality.

Bring the stuff at the bottom of your business intelligence solutions to the top of your to-do list.

If you want to grow a garden, you can choose a location with the best sunlight, plan a layout that allows all the dfferent types of vegetables grow both up and out, till the ground, plant some seeds, and water dutifully. But if you haven't spent the time, energy, and money to learn what kind of soil you have and prepare it with the proper nutrients, then your garden can't grow to full, juicy maturity. You'll get some of the vegetables you hoped for, but many will fail. And you won't really know how much better they could have been, or how many more of them you might have gotten, with a better foundation.

The same is true when you want to grow a BI program. You can plan, design the layout, and start building applications. But if you haven't prepared the foundation of those applications--the data itself--your BI capabilities can't reach full maturity. You'll have some good output, and you'll attack the bad output with the pesticides of ad-hoc standardization or deduplication efforts. And likely, you'll keep going on this way because you won't know how much better your BI could have been with better data.

Or maybe things are worse. Maybe your organization's BI program has actually yielded more pests than plants. When data is inconsistent and incomplete often enough, users abandon the BI solution entirely.

Data quality is critical, but efforts to achieve it just aren't exciting. They're soil, and your organization wants to think about plants. They don't rouse the kind of enthusiasm that BI and analytical applications do. But isn't overenthusiasm one of the reasons your BI program has underperformed? It's time to focus on the soil. It's time to get quality data.

Clarity can help you launch a data quality program that allows your BI applications to produce consistent, thorough, and trustworthy data. We take you through a series of clearly defined steps, each designed to generate quick and measurable ROI. We make it as straightforward as possible so you can get back to implementing the visible BI that your organization wants.

Our data quality services help you:

Get a true picture of current data quality.
Perform an in-depth profiling of the universe of data in your current data stores. Learn where the anomalies, outliers, and other issues are.

Clean the data.
Invest in the data profiling and cleansing tools right for you, and achieve a baseline of consistency and completeness in all your fields.

Define data quality metrics.
Decide on the measures that your organization will use for the hallmarks of accuracy, completeness, consistency, timeliness, uniqueness, and availability. Consider the expectations, acceptability thresholds, and business impacts of each.

Create a data quality scorecard.
Initiate and maintain the tool for determining how you’re doing with respect to data quality and control.

Build a metadata repository.
Identify and store data elements along with their agreed-upon definitions.

Designate data stewards.
Work with a the various business units to identify owners of different types of data, and define their roles and responsibilities for keeping that data clean.

Develop a data maintenance methodology.
Sustain clean data with a process for checking and correcting all new data that comes in. Given that data is growing at unprecedented rates—some studies say your organizational data will double every year—even small error rates cover an enormous amount of data. This task is getting more important every day.

Continuously monitor data quality.
Use data controls at different points in the data processing stream to provide visibility and auditability, and identify failures as early as possible.

Create a channel for reporting data issues.
Tracking and transparency fosters trust in the data.

Remediate the failures.
Define service level agreements in order to mitigate the root cause and minimize downstream impacts within a certain amount of time.

Develop a portal.
Data quality doesn’t have to stay under the covers. Clarity can help you build a front-end portal for data stewards to evaluate, manage, and even correct data flaws.

Build and maintain a Data Quality Center of Excellence.
Give data quality continued visibility by etablishing a hub for exchanging ideas and addressing issues.

If you haven't done so already, implement data governance and master data management.
Data quality needs top-down oversight and support, plus a central system to validate, cleanse, standardize, and merge all your enterprise data.

Contact us for more information.