Evolving Data Maturity: Webcast Series

Data democratization has become a top priority for many organizations. The potential to empower more data users with self-service data access, exploration, preparation and analytics is becoming increasingly appealing. But the right strategy is critical for success, as users will quickly become frustrated without an intuitive way to find, prepare and interact with all the data they need from today’s complex environments.

Watch a panel of experts discuss ways to solve this and other data democratization challenges. You’ll see how to empower users to easily access and work with data while ensuring data governance.

Learn how to:

• Balance self-service analytics with data governance, quality and security
• Leverage data catalogs and metadata integration
• Increase data literacy and build a strong data culture

What if your organization could achieve 3x the ROI related to your data assets? Whether internally focused, externally focused or a combination of both, data marketplaces are helping many organizations quickly extract more value out of the data they already possess and create new business opportunities.

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In this 45-minute session, you’ll get to learn from Doug Laney, recognized authority on data and analytics strategy and best-selling author of Infonomics: How to Monetize, Manage and Measure Information for Competitive Advantage. You’ll hear how data marketplaces in tandem with monetization concepts, such as data scoring and data productization, can yield big dividends.

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You’ll learn about:

• The benefits organizations are experiencing from internal and external data marketplaces
• How data value scoring can support both data democratization and data monetization efforts
• The role of automation and data intelligence to successfully deliver on data marketplace initiatives

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Don’t miss this educational and inspiring session.

Have you heard erwin^® Data Marketplace by Quest^® is now available within erwin^® Data Intelligence Quest^®? Learn more here.

Starting and evolving a data governance program is one of the most important efforts you can invest in to not only govern and protect the data within your organization, but to maximize the business impact of its value. Data intelligence can provide the fuel to help you rapidly mature your data governance effort and show tangible, sustainable results along each step of the way. Attend this 30-minute session and learn: 

• How to measure your organization’s current data governance maturity 
• The key data intelligence capabilities that can support a data governance evolution 
• How erwin by Quest can help you deliver greater data value to the business in 7 steps  

Register today and see how you can use data intelligence to drive governance and deliver data value. 

Want to learn more about the erwin by Quest data maturity model? Get the 7 Steps to Maximizing Your Data Value eBook.

Are you trying to establish an enterprise data modeling and standardization practice?

Attend this on-demand recoding of a live webcast to learn about two essential capabilities you need for a data modeling enterprise solution:

• An intelligent repository – that’s built to manage what you are working on. 
• The ability to share model concepts.

Presentation by: Bert Scalzo, Database Consultant. Bert is an Oracle ACE Alumni, blogger, author, speaker, and database technology consultant. He has BS, MS, and Ph.D. in computer science, an MBA, and has worked for over 30 years with all major relational databases, including Oracle, SQL Server, DB2 LUW, Sybase, MySQL, and PostgreSQL.

Demonstration by: Andreza Silveira Ruiz, erwin by Quest Sales Engineer

If your organization is moving to the cloud, or is already there and wants to improve cloud data governance, you’ll want to watch this on-demand webcast with Danny Sandwell and Tony Mauro from erwin by Quest to learn how to:

• Quickly and accurately document and transform existing data management infrastructures and processes
• Precisely migrate data from legacy, on-premises databases to the cloud
• Automatically find, model, ingest, catalog and govern cloud data assets during their transformation and throughout the cloud lifecycle

You’ll also see a demo of erwin Cloud Catalyst by Quest, a suite of automated cloud migration, transformation management and data governance software and services.

Data modeling is a key facet of data management, and understanding the strengths and purposes of each of the three data modeling types will provide you with a more robust analyst toolkit.

In this webcast, Peter Aiken, an acknowledged Data Management (DM) authority, explores each modeling type to equip you with the knowledge you need to transform data sources into graphical models to document, compare, standardize and enrich their structure and metadata. He covers:

• The key roles that data models play
• How to know when to use conceptual, logical or physical data models
• The rigor of the round-trip data reengineering analyses
• Applying appropriate use of each data modeling type

In this Data Architecture Strategies webcast, Donna Burbank, the Managing Director of Global Data Strategy Ltd. and a recognized industry expert in data management, gives you practical, concrete steps for making business-centered data models that can show immediate value to your organization while building towards a full-enterprise view.

Business-centric data models are important for getting a clear picture of the data that drives the business, like customers, products, invoices, and more. They give business and technical stakeholders a clear, visual way to talk about the important business rules and definitions that drive both operational use of data, analytics and reporting.

No matter what you call it – data munging, data cleansing or data wrangling – everyone agrees that data preparation activities account for 80 percent of analysts’ time, leaving only 20 percent for analysis. Shifting this work to more specialized talent represents a major source of data analysis productivity improvements.

In this session, Peter Aiken, Professor of Information Systems at Virginia Commonwealth University, will discuss the major preparation categories, including collection, evaluation, evolution, access design and storage requirements. Understanding each in context also provides opportunities to develop data governance/ethics frameworks.

You’ll learn how to:

• Transform data preparation from one-off to a more efficient, time-saving process
• Identify and fill data preparation gaps
• Understand the transformations data can survive as it’s prepared for analysis

With business users typically spending 80% of their time on data prep, it can be a challenge to quickly build the data sets you need, especially as more companies look to increase the democratization of their data and shorten its time-to-value.

But it doesn’t have to be that way.

Watch our webinar to learn how, using Toad Data Point Workbook and Toad Intelligence Central, business users can independently:

• Access data from multiple sources
• Query and report on data simply and effectively