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Four key takeaways from our 2015 Data Quality Summit

Yesterday we held our first ever Data Quality Summit in New York City (check out some photos here.) I feel energized from the great insights that were shared, new relationships that were built and interesting conversations that were had during the event. From a discussion on how to monetize data quality efforts, to an engaging panel of clients talking about their use of data as a strategic business asset, the half-day summit was a great opportunity for data-driven professionals to learn more about the industry and share best practices to ensure their organization’s data initiatives are as successful as possible.

There were a lot of interesting presentations and innovative conversations throughout the day. Here are four insights and recommendations I took away from the Data Quality Summit.

1. Develop trust in your data for better insights. If you don’t trust the data your company has and collects, how can you make thoughtful, timely business decisions? To begin transforming to being a truly data-driven organization, you need to understand where your data comes from, and ensure it is valid, complete and accurate. Your data shouldn’t just be “good enough” – you should strive for perfection.

2. Focus on the business use for data. Before beginning any data-related initiative, start by asking why the data is important and what it’s going to be used for. Having a clear understanding of how quality data that is easily accessible will streamline business processes and drive your business forward. This will help you develop a framework of requirements and effective processes to ensure the data is fit for purpose.

3. Be proactive about data quality. Waiting to address data quality challenges until issues arise can result in much larger, more costly challenges. Without a data quality solution in place, your organization will not be able to fully leverage your data asset. Proactive data quality can help you avoid major headaches by ensuring that legacy data is valid and standardized, as well as safeguarding against any new invalid data being entered into your systems.

4. Quantify to drive data quality evangelism. When making the case for data quality and other data-related initiatives, quantifying the need and cost is a straightforward way to gain support for your efforts. Create a justification rooted in facts and numbers that show ROI in order demonstrate the need for your programs. Finding an executive or a member of leadership to sponsor your initiatives is also beneficial.

Interested in learning more about how to build a better foundation for data management and other initiatives? Check out our 2015 Data Quality Benchmark Report

Download the report

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