As organizations and their processes become more interwoven with the Internet of Things, we’ve never had better insight into the cause and effect of business and consumer behaviors. From interpreting marketing analytics and setting up customer newsletters to data security and the ethics of data governance and privacy, we live in a world of accumulated data – with more and more of it every second of every day.
Naturally, just thinking about that truth can be overwhelming. However, there areplenty of tools available to keep you afloat in the sea of data. By implementing proper data management strategies and tools, you will keep your organization focused on its mission and have a plan for what data to store and what data to apply.
In this article, you will learn about:
What is Data Management?
As its name implies, data management refers to the collection, safekeeping, and efficient use of your organization’s data. By understanding how your organization’s data is managed, you can create policies, procedures, and roles to accomplish various tasks. These tasks could include data security and governance, maximizing cost-effectiveness, enforcing accountability, and determining the digital infrastructure that shapes your organization’s network.
While managing data is an inevitable part of modern business, each organization handles information differently depending on its size, the scale of its databases, and the data uses. Still, understanding the purpose of your organization’s data will determine its collection, use, upkeep, and security, which are all necessary to ensure everything else runs smoothly – not to mention legally.
Without adequate data management, data quality suffers, creating other problems such as weak security, redundant access and privileges, and unintentional record duplication or deletion. With that in mind, managing your organization’s data effectively is essential. Otherwise, you run the risk of being crushed by your neglected databases.
As data collection becomes faster and more comprehensive, having a flexible, robust data management system and policies to support it is paramount to your organization’s success. Luckily, plenty of resources and technologies are available such as machine learning, automation, and cloud services to make this task easier.
Data Management vs. Data Governance
The terms data management and data governance are sometimes used interchangeably, but both refer to different aspects of organizational data topics. Data governance is a collection of policies, procedures, and rules that determine how the data within your organization is handled throughout its entire lifecycle. By contrast, data management is how these policies, procedures, and rules are acted upon.
In other words, governance creates the framework, whereas management comprises all the actions within the framework.
For more information:
Types of Data Management Products
With so much data available, it’s vital to determine the correct data management tools to capture, collect, and secure your organization’s sensitive information. Likewise, a wide variety of tools are available to fit organizations of every size and purpose.
Though this list is not exhaustive, these are the main types of data management products you’ll find:
Data Analytics Tools
Regardless of how your data is collected and stored, the next step is always finding ways to apply that information. Data analytics tools do just that; they help collate, analyze, and present data practically for your organization’s members.
For instance, if you are trying to increase website traffic by creating interesting and informative content, Google Analytics provides statistics and data such as:
- The ranking of keywords and pages on your site
- Where your traffic comes from
- How long browsers stay on your site and what pages they visit.
From there, your digital marketing team can make informed decisions about what content to create, what pages to update, or the audience to target within the next paid advertising campaign.
Data Warehouses (DW)
If you collect a lot of data, you need a place to store it all. That’s where a data warehouse comes in handy. A data warehouse collects business-related data and facilitates analytics and decision-making. This can take the form of understanding relationships between data points or tracking trends and patterns in data behavior (for example, tracking user session length to determine which days people are most active).
While data warehouses are a type of data analytics tool, they’re mainly used for large analytical queries or enterprise levels of data.
Cloud Data Management
Gone are the days when organizations are shackled by their local computer hardware capabilities. With more businesses and consumers on the cloud, using cloud computing to your advantage requires effective data management.
This includes determining remote backups, archiving, and recovery of your data, as well as access controls for users trying to use cloud data and any related analytics.
Client Relationship Management (CRM)
CRM software is great for keeping track of past, present, and future clients. In addition, client relationship management databases help collect and store customer contact information, account executive assignments, logging interactions between your organization and the customer, and finding patterns and trends within single records or across large segments of data.
You can then use CRM to analyze marketing and sales campaigns, customer service policies, client retention, and other revenue-generating opportunities such as up-and cross-selling services.
Product Information Management (PIM)
Like CRM, PIM software focuses on collecting, analyzing, and safeguarding product-related data. Product information management is useful for ensuring uniform descriptions, pricing, and inventory management across all your sales channels and updating any distribution or supply chain partners.
For example, PIM can alert a supplier when your inventory of a particular product is low, prompting a new shipment to replenish that product automatically. On the retail side, PIM can push product descriptions, shipping, pricing, and other updates across multiple websites and sales channels instead of having your retail staff manually change each site separately.
Data Management Best Practices
Define the Data’s Purpose
A good rule of thumb regarding data management is that you should only collect data your organization needs to fulfill its business functions. Not only does this eliminate noise and enable your teams to better focus on what’s useful, but it also insists on awareness of why the data is being collected. By understanding the purpose of the data, you can build policies and procedures around it, in essence, using it as a backbone for your business model and the reliant processes.
Identify Data Ownership
Just as you should identify why you’re collecting data, you should find the experts in your organization who can ensure its quality, storage, and application. When determining data owners, look to the senior staff and team leads who know what the data should look like to be the most useful for their jobs. Similarly, data owners provide a much-needed layer of accountability to minimize risk and maximize reaction speed to incidents if anything goes wrong within the database.
Establish and Enforce Uniform Data Conventions
Standardization is an essential facet of keeping a valuable, hygienic database. Without it, data can quickly go missing, become duplicated, or affect search queries negatively. Especially if you have an international team, something as simple as date formatting can cause unnecessary confusion. For instance, does 06-07-2022 mean July 6th, 2022 or June 7th, 2022? That said, make sure to establish uniformity in file naming and formatting conventions to ensure everyone understands the data.
Use Layered Security Measures and Practices
No matter how you organize, use, and interact with the data, consider having multiple layers of security to keep it safe. Everything from strong passwords, encryption, and access controls to using proxies and data masking are good tools based on your organization’s needs and the sensitivity and scale of the data it handles. Depending on your jurisdiction, you may also be required to implement specific security procedures by law, so including them also ensures your organization’s compliance (and avoids fines and other penalties).
Revisit Data Management Policies Regularly
As data and the way it’s used evolves over the lifespan of your organization, be sure to update your data management policies regularly. Since every organization has different needs, finding the right balance is important. Too infrequently and your procedures become outdated and unuseful; too frequent and you’ll drive your staff insane trying to keep up with all the changes – not to mention the lost time from constantly readjusting. Instead, consider quarterly or semi-annual reviews and make minor adjustments over time to keep the data, its storage, and management policies in top shape.
Implementing Data Management with Satori
Satori provides a DataSecOps solution that simplifies implementing and maintaining data management. Satori provides continuously discovery and masking of sensitive data, enabling easier data management.
Learn more:
- Guide: Data Management Guide
