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With Modernization Comes Data Challenges

Modernization is driving many of today's enterprise data strategies—and cloud stands out as the primary vehicle for attaining this modernization. However, many enterprises are struggling with data quality issues, as well as integrating cloud-based and on-premise data. Read More

DBTA 100 2020: The Companies That Matter Most in Data

Today, there is a constantly evolving list of data management issues that organizations are contending with. In addition to pressures of exploding data volumes, there is urgent demand for real-time data-driven insights as well as more widespread data access. Expanding regulatory mandates also demand greater data quality and governance, as do cybersecurity threats. Whether cloud-based or on-premise and open source or proprietary, there are many options for data management and analytics. Spanning the spectrum of well-established and cutting edge, the DBTA 100 list recognizes companies that are innovating and preparing for the future. Read More

Data Summit Connect 2020 Keynote Explores Data Collection and Privacy in the Age of COVID-19

Data Summit Connect opened up on June 9 with a keynote from Lee Rainie, director, internet and technology research, Pew Research Center and Author of the book "Networked: The New Social Operating System," who discussed how the current pandemic is affecting data collection and privacy. Read More

6 Steps to Win with Data: First, Get Out of Denial

What more companies need today is a "data lab" to create ideas from data and a "data factory" to turn those ideas into products. Google, Amazon, and other data-driven giants already work like this. So should companies outside of technology.  Read More

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Todd Schraml

Database Elaborations

Todd Schraml

  • The Importance of Canonical Data Models An enterprise conceptual data model is often seen as a high mountain to be climbed, a journey that will last a lifetime. People have visions of 10 feet or more of wall in the corporate offices wallpapered with an entity relationship diagram [ERD] that has zillions of teeny, tiny boxes and more relationship lines than the combined lines of queuing patrons in all Disney Resorts, when full. In this context, an enterprise conceptual data model is a daunting task not to be taken lightly. But in today's world, that enterprise conceptual data model can simply be a list of subject areas.
Recent articles by Todd Schraml
Craig S. Mullins

DBA Corner

Craig S. Mullins

  • Development DBAs Versus Production DBAs Both development and production database administration are required to support database applications. However, it is not usually necessary to have different DBA staffs to perform the different roles. Indeed, intimate knowledge of how a database application was developed can make it easier to support that application once it becomes operational in the production world. But the bottom line is this: You will need to define, plan for, and staff both development and production DBA roles in order to create useful database applications.
Recent articles by Craig S. Mullins
Kevin Kline

SQL Server Drill Down

Kevin Kline

  • Keep Up With the Latest SQL Server Updates Here's one big advantage to moving to Microsoft Azure SQL Database—you never have to patch. That's all well and good, but most of the SQL Server installed license base is still on-premise. If you're in this category, then it is essential that you keep up with patching and security fixes regularly. The information in this article is the sort that experienced SQL Server DBAs keep close at hand. So, let's take a few minutes to walk through the details of how to do that.
Recent articles by Kevin Kline
Guy Harrison

MongoDB Matters

Guy Harrison

  • MongoDB 4.4's Most Critical Features This year, an in-person MongoDB World conference in New York City was inconceivable. With NYC and the world still in various levels of COVID-19 lockdown, MongoDB World was held in the cloud as a virtual event—MongoDB.Live—in the first week of June. Holding the annual conference in the cloud is quite apt in many ways.
Recent articles by Guy Harrison
  • The Growth of PostgreSQL as a Tier-1 RDBMS While Postgresql.org has been around since 1996, its origins go back to the mid-1980s, when Michael Stonebraker, who led the Berkeley team that developed Ingres, started a new project called Postgres to build upon the ideas in Ingres. While most PostgreSQL users rely upon the free and open source implementation, there are several variants.
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