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Designing an ETL Design Pattern

Cars all have steering wheels, brake and gas pedals, doors, and engines. These characteristics are what combine to create a pattern. Because of this pattern every auto manufacturer can invest more substantially into the realm of innovation—what makes their car different or better. Similar to automobiles, this is a goal of software patterns, to embrace innovation and reap the benefits of reuse. Read More

Registration is Now Open for Data Summit Connect 2021

Overcoming travel challenges, Data Summit Connect 2021, presented by DBTA and Big Data Quarterly, is a virtual event that will run May 11-12 and include provocative sessions, exhibits, and opportunities to network. In addition, preconference workshops will be held on May 10. Read More

7 Strategies to Prevent Cracks from Forming in the IoT Security Wall

The Internet of Things (IoT) is all around us—from baby monitors and home security cameras to smart vehicles, smart power grids, and even the emergence of smart cities. In recent years, the IoT has, and continues to transform how we, as individuals, live and work. Read More

Why Now is the Time to Embrace the Next Generation of Enterprise Architecture

Today's organizations often have more information at their disposal than they know what to do with. From products and apps to processes, departments, data, and more, there's so much that should be considered every time a business takes on a new change project, considers a new solution, or begins a major digital transformation. Before organizations embark on any of those journeys, they must understand how to get from their current state to where they ultimately want to end up. Read More

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Columnists

Todd Schraml

Database Elaborations

Todd Schraml

  • Change and Not Change is Ultimately Zen in Action All data architects should con­sider themselves change agents for the organiza­tions in which they work. But at the same time, business also wants to keep much the same. Such discoveries can be confusing when business is say­ing that change is desired, but their actions seem focused on preventing change. It can suggest the Albert Ein­stein quote (or the Baba Ram Dass quote, based on which version of history one sub­scribes to) that "We cannot solve our problems with the same thinking we used when we created them."
Recent articles by Todd Schraml
Craig S. Mullins

DBA Corner

Craig S. Mullins

  • The Importance of Data Modeling in a Big Data World You would think that with the towering importance of data in today's modern organization that data modeling would be viewed as extremely important by management and IT professionals, so it is somewhat ironic that the age of big data has coincided with a long-term slide in data administration and modeling in many organiza­tions. This is not a situation that should continue to be tolerated.
Recent articles by Craig S. Mullins
Kevin Kline

SQL Server Drill Down

Kevin Kline

  • Change and Not Change is Ultimately Zen in Action All data architects should con­sider themselves change agents for the organiza­tions in which they work. But at the same time, business also wants to keep much the same. Such discoveries can be confusing when business is say­ing that change is desired, but their actions seem focused on preventing change. It can suggest the Albert Ein­stein quote (or the Baba Ram Dass quote, based on which version of history one sub­scribes to) that "We cannot solve our problems with the same thinking we used when we created them."
Recent articles by Kevin Kline
Guy Harrison

Emerging Technologies

Guy Harrison

  • Dremio Reinvigorates the Data Lake There's still life in the data lake concept, as evidenced by the growing success of Dremio. Dremio describes itself as "the cloud data lake" platform. It provides a cloud-based engine that layers over cloud object storage such as Amazon S3, Azure's Data Lake Storage, or even legacy Hadoop systems.Why would Dremio succeed where Hadoop ulti­mately failed?
Recent articles by Guy Harrison
  • Cleaning Dirty Data Remember, all data is dirty—you won't be able to make all of it perfect. Your focus should be on making it good enough to pass along to the next person. The first step is to examine the data and ask yourself, "Does this data make sense?" Data should tell a story or answer a question. Make sure your data does, too. Then, before you do anything else, make a copy—or backup—of your data before you make the smallest change.
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Trends and Applications