Improve Self-Service Analytics Credibility with Data Quality

 

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Improve Self-Service Analytics Credibility with Data Quality In the journey to become more data-driven in decision making, we are seeing unprecedented democratization of data and adoption of self-service analytics. Rigid data collection and reporting processes of the past have given way to rapid gathering of raw, unstructured and crowdsourced data. As a result of that change, there are inevitable trade-offs with data quality. Self-service visual analytics solutions often quickly expose data quality issues that you may not even realize exist. Unfortunately, inaccurate data undermines the powerful value of self-service analytics. If people don't trust your reports, they won't use them. Since self-service analytics credibility, adoption and success hinges on accurate data, data quality should be given more attention as you implement these solutions. Learn More Additional Resources The Definitive Guide to Selecting the Right ADC The Top 6 WAF Essentials to Achieve Application Security Efficacy SUBSCRIPTION SERVICES You are currently subscribed as jonsan98@gmail.com If you do not wish to receive future mailings from Networkworld Resources, unsubscribe. When accessing content promoted in this email, you are providing consent for your information to be shared with the sponsors of the content. Please see our privacy policy for more information. Copyright 2017 | Networkworld | 492 Old Connecticut Path | Framingham MA 01701 | www.networkworld.com.