Do you have a data quality alliance strategy?

Whether you’re embarking on a data quality mission for the first time or your presence is well known, it never hurts to have allies throughout your organization. By finding and gaining these supporters, you can gain influence and achieve your data quality goals. It may be difficult due to the many intersecting groups and initiatives, but the results are well worth the effort.

When I started working in data quality more than 20 years ago, the big problem I faced was getting traction in a small organisation. I knew we needed to make improvements, but it was hard to get the mandate from senior management.

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Healthcare, big data and big frustrations

As part of The Affordable Care Act, many Americans have had to change insurance providers or plans. I’m old enough to realize that wide-sweeping changes like this legislation will surely face many legal, technological and financial obstacles; I've even talked about some of these issues before. Suffice to say, I didn’t expect a new policy that affects every American would be carried out without significant challenges. I just never anticipated basic communication would be one of them.

Let me explain. Read More »

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Facing ethics in a data-driven world

I have previously blogged about how the dark side of our mood skews the sentiment analysis of customer feedback negatively since we usually only provide feedback when we have a negative experience with a product or service. Reading only negative reviews from its customers could make a company sad, but could reading only negative status updates from your friends on a social network make you sad?

Facebook decided to find out by running an experiment on almost 700,000 users in early 2012. In late 2013, they published the results in the Proceedings of the National Academy of Sciences (PNAS) with a research report entitled Experimental evidence of massive-scale emotional contagion through social networks. Facebook first used sentiment analysis to determine the general mood of status updates (in addition to the mood status that Facebook provides to allow users to convey what mood they are in as part of a status update). Facebook then used mood to intentionally filter what users saw in their newsfeed for one week. Based on the mood of the status updates these users posted during the experiment, the research revealed that users who saw fewer positive updates became sad and users who saw fewer negative updates became happy.

The reaction to these published findings, however, was neither happy nor sad but mad, since these Facebook users were experimented on without their knowledge.

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Cracking the code to successful conversions - establishing an issue management process

Issue management defines the process of documenting and escalating any issue that the project may encounter during development, testing and implementation into production. The process document could include the following:

1. How does the project find the issue? Usually, an issue is reported by one of the business users or conversion team members.

2. How does the project document the issue? Some projects use software, and some use spreadsheets. Check the corporate requirements for this type of documentation. The client may already own this type of software.

3. How does the project resolve the issue? This would include how an issue is communicated to the team for resolution, as well as how information is communicated to the business users and the business sponsor. Check the communication plan for more information on escalation. Read More »

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Three ideas for communicating data quality success

You have kicked off a data quality initiative and had some great results. Your next goal is to build on this success and grow the influence of your team around the organisation.

To achieve this, you need to get creative and put on your marketing hat. Here are some ideas that past interviewees on Data Quality Pro have shared with me when quizzed about their communication strategy.

1) Host an annual data quality event or summit

One of my recent interviews was with a data architect in a large lifestyle media organisation. To help engage the business, they are creating a data summit to help the business learn more about the potential of its data and how they can get involved.

This is an excellent idea for any company that wants to showcase some of the data quality projects they’ve been successfully delivering.

For global organisations it also offers the opportunity to host virtual events or invite members from overseas to observe how the data quality vision is maturing. Read More »

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On data, risk and LeBron

Few cities use data as much as Las Vegas. Walk into any casino and you'll see nothing sort of a paean to data. For instance, blackjack dealers use zero discretion when flipping cards. Pit bosses scour for potential cheats looking to move the needle just a few degrees. And that means you, Ben Affleck.

It should be no surprise, then, that many Vegas casinos took extreme action in light of LeBron James' decision to become a free agent on June 24, 2014. As Darren Rovell of ESPN wrote in LeBron opt-out impacts Vegas books:

As news of LeBron James opting out of his contract with the Miami Heat on Tuesday morning spread, some insiders in the gambling world took the ultimate measure to minimize their risk. They pulled all future odds on all NBA teams to win next year's title. Read More »

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Data science and decision science

Data science, as Deepinder Dhingra recently blogged, “is essentially an intersection of math and technology skills.” Individuals with these skills have been labeled data scientists and organizations are competing to hire them.

“But what organizations need,” Dhingra explained, “are individuals who, in addition to math and technology, can bring in the right business perspective. These individuals must have the ability to artfully blend left-brained and right-brained thinking to solve complex business problems. They should possess the requisite analytical skills to understand, translate and generate insights that can then be consumed effectively.” Dhingra refers to them as decision scientists who complete the data-driven decision making process started by data scientists. Read More »

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Examples of using graph analytics

Over the past few weeks I have been discussing the use of graph models for analyzing interconnectivity and how entity characteristics can be inferred in relation to links and connections. While we looked at the social network domain for identifying influential individuals within a social community, there are numerous other opportunities for examining the relationship between entities and identifying actionable knowledge. Here are three common examples:

  • Mobile telecommunications network optimization: Mobile telecommunications companies seek to make the best use of their network in a number of ways, including ensuring the quality and continuity of calls (so that calls are not dropped in the middle of connections), providing equal distribution of bandwidth (to prevent any particular section of the network from being overloaded), and eliminating dead zones (where there is little or no connectivity). Read More »
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Cracking the code to successful conversions - review or define standards

It is important to review any existing documents (maybe from previous projects) before re-inventing the wheel (standards and guidelines). My preference is to review existing standards with my customer and recommend any enhancements or additions that may be required for the conversion project. Consider locating the following:

1. Infrastructure guidelines - Usually found via the technical staff (systems personnel). Review for any gotchas, and include a report on usage of the intended platforms.

2. Database guidelines - Usually found via the database administrators or keepers of the production databases. This could be internal or external people.

3. Data modeling standards and guidelines - Usually found by talking with the enterprise data modeler or the manager of data management, and should include naming standards and entity/attribute definitions. Read More »

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