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TDWI Upside - Where Data Means Business

Best Practices to Address Today’s Data Management Challenges

These four best practices will guide your CDOs and other database management leaders to develop effective, modern data management practices.

Today, the world produces as much as 2.5 quintillion bytes of data per day. Although this is a treasure trove of potentially valuable information and insights, these massive amounts of data also present challenges for enterprises in storing, sharing, cleaning, protecting, and leveraging data efficiently.

For Further Reading:

The Age of Enlightenment in Cybersecurity

Assessing Your Cybersecurity Risk: Why, What, How?

How Global Turmoil and Inflation Will Impact Cybersecurity and Data Management in 2023

As chief data officers, data engineers, and others involved in addressing these challenges search for optimized database management solutions, there are specific best practices that will overcome these challenges, allow you to get ahead of the curve, and anticipate your enterprise’s possible future data needs.

Optimizing database management and harnessing the powerful predictive and prescriptive potential of AI are critical success factors for today’s enterprises to compete and win. With this in mind, here are four best practices to guide your CDOs and other database management leaders to develop their data management practices.

Best Practice #1: Align database management with enterprise business goals

Most database teams focus primarily on creating customer profiles as a guide for data collection and analysis. They should also consider creating profiles of end users, partners, and other potentially important audiences, both to get a sense of their total market and as a hedge in case enterprise teams decide to leverage this information later.

Database teams should also work with other teams to better utilize data by developing analytics processes to study key business decisions in areas such as product development, acquisition strategy, and financing activities. Part of this effort includes focusing trend analysis on issues central to the success of the organization, ongoing analysis of competitors, usage trends of the enterprise’s products, and related areas. Analysis of the enterprise's processes and procedures can identify potential automation and other streamlining opportunities.

Best Practice #2: Constantly focus on security

If your database management team isn’t thinking about continuous improvement to your cybersecurity strategy every minute of every day, they should be. Hackers are continuously devising new ways to breach enterprise networks, whether through employees’ mobile devices, by attacking APIs, or even penetrating basic technology such as messaging systems. The optimal cybersecurity “stack” (firewalls, instruction prevention/detection, security information and event management, and related solutions) will vary from enterprise to enterprise, but every enterprise should regularly complete these four steps:

  • Build a comprehensive maintenance and update plan. Keep up with software patches and other routine maintenance that can prevent some types of breaches.

  • Practice the backup and recovery plan regularly. This will ensure teams identify and fix any gaps or weaknesses in the plans before a hacker finds them.

  • Train your teams. When teams get busy, training often falls by the wayside, but it shouldn’t! Threat vectors change regularly, and hackers are always looking for new ways to exploit weaknesses. Teams need to stay up to date on the current cybersecurity trends.

  • Employ automation. Automation can help alleviate the burden on teams by performing tasks such as automated backups.

Best Practice #3: Reduce data duplication

Duplicate data can lead to wasted internal resources and potentially redundant efforts (e.g., a team might take action twice because they think duplicated data represents two separate situations). Teams should focus on reducing data duplication by educating their employees about data quality. Many employees don’t understand the potential problems of creating duplicate records.

Eliminating data silos managed by different groups within an organization also reduces the potential for data duplication. Data silos can also be problematic because each database team may not follow enterprise-wide guidelines for maintenance and security standards. It is important to test the database regularly, searching for duplications to ensure the team is managing this issue effectively.

Best Practice #4: Democratize data accessibility

Managing and protecting data are critical functions, but data must also be accessible to enterprise users. Organize data to take into account the user experience (UX) to optimize efficiency. Ask users periodically for feedback on their database experience; this can take the form of a survey or creation of a committee made up of database management team members and data users.

A Final Word

Database management best practices arm organizations with the ability to use data to gain better insights faster, which in turn improves an enterprise’s competitive position. Successful teams will apply these best practices consistently and comprehensively to avoid allowing the sheer volume of data available to overwhelm them. Of particular importance is building and updating a cybersecurity stack that will prevent intruders from breaching the network and causing chaos with the data.

Involving data users will help ensure database management teams make data accessible and improve the user experience. This focus on database management strategy and process clearly requires a significant amount of effort, but it will pay short- and long-term dividends by ensuring the accuracy, safety, and value of this critical asset.

About the Author

Max Liu is the co-founder and CEO of PingCAP. He has over a decade of experience in system infrastructure and software technologies. He is also the co-author of the opensource projects TiDB, TiKV, and Codis (an open-source Redis cluster solution). You can contact the author via email, Twitter, or LinkedIn.

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