Why Data Analytics Projects Miss the Mark

Posted in: Uncategorized - Oct 31, 2016

For many organizations, existing data-analytics infrastructures are too complicated, and it's difficult to find qualified job candidates to helm analytics

Big Data Management Best Practices for Data Lakes

Posted in: Business Intelligence - Oct 27, 2016

Organizations are pursuing data lakes in a fury. Organizations in many industries are attempting to deploydata lakes for a variety of purposes, including the persistence of raw detailed source data, data landing and staging, continuous ingestion, archiving analytic data, broad exploration of data, data prep, the capture of big data, and the augmentation of data warehouse environments. These general design patterns are being applied to industry and departmental domain specific solutions, namely marketing data lakes, sales performance data lakes, healthcare data lakes, and financial fraud data

Making Data Preparation Faster, Easier, and Smarter

Posted in: Business Intelligence - Oct 25, 2016

Business users, business analysts, and data scientists have diverse data needs and specialties, but they all have one thing in common: they are tired of long, complicated, and tedious data preparation. Unfortunately, data preparation is getting even more difficult as users doing analytics and data discovery reach out to larger volumes of different types of data. top

Gartner Critical Capabilities for Data Quality Tools

Posted in: Master Data Management - Oct 20, 2016

Download this Gartner report to see how 18 data management technology vendors stack up when comparing performance across the most significant use cases for data quality

Dynamic Metadata: Enabling Modern BI Architecture

Posted in: Business Intelligence - Oct 20, 2016

In a highly competitive market, today’s forward-looking organizations are seeking to optimize and modernize their IT investments, specifically in enterprise business intelligence (BI). There’s a strong push to capitalize on newer features such as self-service BI, advanced analytics, and customized visualizations—all of which relinquish the centralized data governance necessary for corporate and regulatory compliance. top

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