metadata-mq
  • FIMA: Modernizing Data Quality & Governance. Unlocking Performance & Reducing Risk

    This paper will evaluate how financial services companies are managing the challenges posed by data quality management. By analyzing which data types and data characteristics businesses are struggling with, we will uncover the true business costs associated with data quality. We will also gauge how data governance programs are maturing and how they are being measured. Finally, we will asses how data is being managed within financial institutions.

  • Mitigating Risk in Master Data

    This paper reviews how risk can be mitigated withing master data environments by identifying, analyzing, protecting and monitoring sensitive data.

  • Address Validation: Best Practices for Interpreting and Analyzing Address Data Quality Results

    Inaccurate addresses can be a costly problem for your organization and not just because they prevent prompt, accurate delivery of mailed communications. Correcting them manually involves significant time and expense while still leaving room for human error. This white paper offers best practices for interpreting and analyzing the results generated by Informatica AddressDoctor, which uses reference data from reputable sources to evaluate the accuracy and deliverability of physical postal addresses.

  • So verwandelt Big-Data-Management Petabytes in Profite

    Erfolgreiche Big Data-Projekte basieren auf drei wesentlichen Säulen,Erfolgreiche Big Data-Projekte basieren auf drei wesentlichen Säulen: Dynamische, optimierte Big Data-Integration, Durchgehende Governance und Qualität für Big Data

  • Great Data – The Key to Building and Sustaining Customer Relationships

    In an ideal world, marketers would leverage their data to identify, segment, and target customers and prospects when and where they are most likely to respond, and with the best possible messaging to drive engagement, response, and sales conversations. Marketers don’t live in that ideal world. Garter finds that 82% of CMOs don’t feel prepared to deal with large sets of data. How can data enrichment help marketers get to that ideal world/overcome these challenges? See how to put data to work for you, the key challenges you need to understand, and how to solve these challenges with a strategy that combines data infrastructure and the content of your data itself.