Achieve Governed Self-Service Analytics at Scale
sponsored by Tableau Software
WHITE PAPER:
Uncover 4 steps for successfully deploying governed self-service analytics so that you can meet the growing need for self-service analytics while still ensuring a high standard of data governance, trust, security, and monitoring.
Posted: 09 Aug 2017 | Published: 09 Aug 2017
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How to Operationalize Machine Learning and Data Science Projects
sponsored by IBM
ANALYST REPORT:
Companies everywhere are relying on data science to solve business problems. However, many data scientists and engineers lack the skills to successfully operationalize data science models. Read this research report to learn how your organization can successfully operationalize machine learning and data science projects.
Posted: 12 Nov 2018 | Published: 12 Nov 2018
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Vlamis Software Solutions Shows Enterprise-Changing Results with Oracle Autonomous Data Warehouse
sponsored by Oracle Corporation
WEBCAST:
Watch this webcast to learn how 2 tech companies worked together to incorporate Oracle ADW into their model, making data and insightful analytics available for even the non-technical members of their teams.
Posted: 10 Jan 2019 | Premiered: Dec 31, 2018
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Your Essential Guide to Modern Data Integration
sponsored by Information Builders
WHITE PAPER:
Read this white paper to learn how to work around the data governance process knowledge disconnect between IT and business users and achieve modern data integration.
Posted: 01 Mar 2019 | Published: 31 Dec 2018
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Big Data Analytics: How to work smarter with data-driven insights
sponsored by ComputerWeekly.com
EGUIDE:
In this e-guide, learn about the state of adoption of data analytics in Australia, how Commonwealth Bank is making analytics tools more accessible to small companies and how SAS is prepping its marketers for the data flood.
Posted: 02 Jun 2017 | Published: 02 Jun 2017
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Top 10 Data Mining Mistakes
sponsored by SAS
WHITE PAPER:
In the following paper, we briefly describe, and illustrate from examples, what we believe are the “Top 10” mistakes of data mining, in terms of frequency and seriousness. Most are basic, though a few are subtle. All have, when undetected, left analysts worse off than if they’d never looked at their data.
Posted: 07 Apr 2010 | Published: 07 Apr 2010
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Ten Things to Avoid in a Data Model
sponsored by CA ERwin from CA Technologies
WHITE PAPER:
The construction of a data model is one of the more difficult tasks of software engineering and is often pivotal to the success or failure of a project. Many factors determine the effectiveness of a data model. In this white paper, industry expert Michael Blaha covers the Top 10 pitfalls to avoid — from both the strategy and detail perspective.
Posted: 19 Oct 2010 | Published: 01 Aug 2010
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Improving Data Quality Through Data Modeling
sponsored by CA ERwin from CA Technologies
WEBCAST:
Explore with William McKnight the factors involved and how organizations should go about valuing data quality through modeling and taking the right steps to remediate data quality defects throughout the enterprise.
Posted: 20 Oct 2010 | Premiered: Jul 22, 2010
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Business-Model-Driven Data Warehousing: Keeping Data Warehouses Connected to Your Business
sponsored by Kalido
WHITE PAPER:
This paper analyzes the issues of conventional data warehouse design process and explains how this practice can be improved using a business-model-driven process in support of effective Business Intelligence.
Posted: 04 Jun 2008 | Published: 01 Jun 2008
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Avoiding Data Quality Failure: Identifying Data Quality
sponsored by Pitney Bowes Business Insight
PRESENTATION TRANSCRIPT:
This presentation transcript features speaker Evan Levy, partner and co-founder of Baseline Consulting, a professional services firm concentrating on enterprise data issues. This discussion is about data quality and some of the challenges and pitfalls that are seen during data quality implementation.
Posted: 05 May 2009 | Published: 03 Mar 2008
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