Friday, May 17, 2024

What is Big Data Management?

Datamation content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.

Big data management refers to the governance, administration, and organization of the enormous volumes of data companies handle throughout its lifecycle, including ingesting, processing, storing, and analyzing it to fuel decision-making and keep operations running smoothly. Because big data management touches on many areas of an enterprise’s work, it takes time and a concentrated effort to create and stick to an effective action plan. This article provides an overview of the different components of big data management, its benefits and challenges, and some of the most common techniques and best practices. It also explores the services and vendors available to help businesses with their big data management efforts.

What is the Importance of Big Data Management?

Big data management concerns how organizations store and handle data. Adherence to best practices can make costs more manageable and ensure businesses have the appropriate infrastructure for retaining information now and in the foreseeable future, making it easier to scale up as needed or maintain the proper security for personal or confidential data.

Done right, big data management ensures that an organization’s data is accessible, well-organized, and accurate. It’s essential for increasing people’s trust in the information they rely on for decision-making. Advanced analytics platforms won’t give reliable results if the data is inaccurate—crafting and enforcing well-defined guidelines for processing and handling data ensures an organization’s data is consistent, accurate, and secure.

A focus on data governance as part of big data management can protect an enterprise by limiting the damage of a security breach or similar problem, and reduce regulatory issues by ensuring compliance with legal or jurisdictional data policies—for example, the European Union’s General Data Protection Regulation (GDPR), which has stipulations that allow people to see the information organizations have about them.

The volume of data organizations collect and store has never been higher, and it’s only growing. Enterprises that don’t have proactive strategies for managing that data will find it difficult to catch up and risk damaging their operations or reputations, and potentially legal or regulatory issues.

Read Big Data Analytics to learn more about how organizations are working with the data they collect.

Big Data Management Challenges

The sheer volume of data presents the single biggest challenge when it comes to big data management. Unstructured data—data like emails, social media content, and multimedia—presents different challenges than structured data like spreadsheets and database records, and in aggregate, managing so much data in so many different formats from so many disparate sources requires strategy.

Organizational silos complicate those efforts, upping the risk of duplicate or hidden information or inconsistencies in how data is collected, formatted, or stored.

Managing big data can become even more daunting if organizations don’t implement scalable plans for handling incoming spikes. For example, many organizations are especially busy during specific types of the year—it’s more challenging to efficiently and effectively use the additional information associated with those periods if leaders haven’t planned for the anticipated surges.

Big Data Management Benefits

Big data management allows businesses to remain competitive and feel confident about the information they use to make critical decisions. It also provides a number of additional benefits—here are the most common.

  • Scalability–data management lets businesses create repeatable processes to increase or decrease systems based on data needs, providing predictability and minimizing costs.
  • Security–effective policies for how data is stored and who can access it can ensure data is backed up, recoverable, and protected from unauthorized access.
  • Accessibility–by maintaining consistent approaches to collecting, formatting, and storing data, organizations make it available to the right people at the right time.
  • Accuracy–big data management can increase trust in data across an organization by ensuring it is accurate and reliable.
  • Compliance–data retention and privacy policies help keep an organization in line with jurisdictional and legal regulations, ensuring compliance and preventing privacy concerns.

4 Big Data Management Best Practices

Big data management is most effective when it follows industry standard best practices. Here are some to strongly consider, regardless of organization type or size.

Know Which Data to Prioritize

The time and money organizations must invest in big data management typically increases alongside information volumes. Businesses should identify the information that is most important and create data retention policies for how—and how long—to retain it as well as what data should be purged to minimize storage costs and reduce time spent searching.

Create Backup and Recovery Strategies

All big data management efforts should include steps to keep data safe from cybersecurity threats, natural disasters, or storage failures. Regular backup and recovery plans are a critical part of any big data management strategy.

Understand the Types of Data You Have

All data falls into one of three categories: structured, unstructured, or semi-structured. Structured data includes numbers or text strings that relational databases can handle, while unstructured data is more varied and can consist of information stored in audio files, images, or videos. Semi-structured data contains characteristics of structured and unstructured data. Most organizations have significantly more unstructured than structured data. Knowing how to store, access, and work with the right kind of data is key.

Establish Data-Handling Processes

Much of an organization’s data will arrive for processing in various formats and from different sources. Proactive processes for evaluating, cleaning, and formatting it can ensure consistency and reduce errors. Making data-handling improvements may involve following steps to standardize the information’s format or screening it for duplication problems.

Bottom Line: Implementing Big Data Management

Big data management is essential for enterprises as the volumes of data-–and the importance of its role in operations—skyrockets. Tackling it can be complex. A number of providers offer services to help with enterprise big data management, from auditing existing processes and making detailed recommendations to outsourcing data management strategies and procedures entirely. They can also help create action plans for moving data between locations, such as from on-premises solutions to the cloud.

Other vendors offer data management tools aimed at taking much of the burden off of enterprises.

Microsoft Azure, Google Cloud, and Amazon Web Services (AWS) all offer products to move, store, and analyze data, and IBM offers artificial intelligence-powered products to facilitate big data management and improve decision-making.

Whether in-house, outsourced, or a hybrid model, all enterprises should be fully engaged in a big data management strategy that protects, improves, and assures the reliability of its most valuable asset.

Read Top 7 Data Analytics Tools and Software to discover the best platforms for working with and visualizing data.

Subscribe to Data Insider

Learn the latest news and best practices about data science, big data analytics, artificial intelligence, data security, and more.

Similar articles

Get the Free Newsletter!

Subscribe to Data Insider for top news, trends & analysis

Latest Articles