The recipe for smart data management

Successful companies thrive on data, but what happens when there is too much data? Too many organizations are drowning in a sea of ​​data from the information they create, collect and receive from sensors and devices.

An overabundance of data eventually obscures business operations, making it difficult to realize true value and involving risk and high costs.

Where previously only data architects and database managers were solely responsible for managing data, it is now everyone’s business. Data management is now shared by any business professional that generates, shares, uses and stores huge amounts of data every working day.

How can you help your employees understand the need for good data management to protect critical data from loss or theft? How can they know the difference between valuable and redundant data? And how can they understand the entire lifecycle of data as it moves through multiple departments, devices, and people?

The answer lies in the ability to understand and apply intelligent data management. If your organization struggles to survive in a sea of ​​data, here are six steps to help your employees learn how to manage data and gain essential insights to help your business grow.

Know where and how to find data

Most of us know how to find data in our applications and shared file systems like DropBox or other cloud-based storage services. But often that data is tribal and limited to our roles or departments. According to IDC, for every 1,000 people in an organization, an average of $5.7 million in labor costs every year is wasted looking and not finding data.

A data review helps expand visibility beyond our primary roles and groups to discover how much data is in motion and at rest. This assessment provides an overview of data that can help emphasize its value, reduce the risk of loss or theft, and estimate the costs, stages, and timeliness of any associated projects.

The assessment starts by discovering primary storage resources for databases and unstructured data silos across your organization. Primary storage can exist in on-premises servers, DAS/NAS/SAN resources, cloud-based data warehouses, and data lakes.

Unstructured data can exist in endpoints such as devices, shared drives, email servers, files, emails, chats, and application data. In some large organizations, up to 80% of the data is unstructured, can sit outside a database, and can never be analyzed.

Identify your data

Once you have a clear picture of where your data resides, you need to determine what kind of data you are managing. Some of your data can be identified by your databases. But the most important discoveries are to be found in pools of unstructured data.

Intelligent data management requires rapid and effective data classification and identification across your enterprise. You should label data sources and elements with metadata to provide context in how each data should be organized and treated. By indexing your data with metadata labels, you identify network addresses, geolocations, and essential attributes of each date, such as file names, timestamps, types and sizes.

Practice basic data hygiene

Once you know your data, you can start cleaning it. Data hygiene practices help mitigate data sprawl that creates unnecessary costs, process friction and risk. This usually starts with searches on your data assets to identify duplicate files and orphaned data.

You can then create data hygiene policies that assign targets to complex queries. For example, a policy might be to clean up trash files or delete duplicate files. The policy may provide a limited list of data, free of human error and highly desirable criteria to enable further action.

Secure your data ecosystem

Your data security concerns are likely related to industry regulatory compliance and cybersecurity threats. Intelligent data management practices can include both.

Robust monitoring and authorization of security events, identity and access controls are good starting points for securing corporate data. But these tools must also quickly inform data stakeholders about incoming threats, latent or introduced data vulnerabilities, and potential privacy or compliance issues.

Decide when and how to securely lock or delete data. Compliance and security issues need to share a decision workflow for data on-premises and in the cloud or across services. These decisions should relate to what data should be retained, whether it is essential to conduct business or necessary to meet the company’s compliance mandates. For example, financial data for a SOX audit must be kept for seven years, while GDPR statutes in Europe require user data to be deleted as soon as it is no longer needed.

Optimize your data

Most organizations use a variety of applications to move and store data. For example, their inventory may include cloud-based repositories, software-as-a-service (SaaS) based productivity apps, streaming data services, or backup and recovery tools.

Rather than ripping and replacing essential tools, intelligent data management should fully index the data within these sources and destinations to improve optimization.

Take advantage of your data

In general, excess data increases costs and risks. But we also know that data is essential for enterprise organizations to survive and thrive. To maintain this balance, you need to extract maximum value from your data, whether it’s used to make employees more productive, improve our strategic insight for better decisions, or deliver newer and learning services for customers.

This requires you to tailor data to your organization’s most critical use cases and then continue to optimize other critical processes. For example, a pharmaceutical research company may prioritize machine learning, while a real estate insurance company may lean on improving incident management and resolving claims.

Optimize your data to provide powerful queries and application query responses that meet employee and customer demands in every use case, and achieve greater ROI.

You are then ready to set policies for copying, moving, archiving, retrieving, and deleting data, which are more adaptive and responsive to those workloads.

Intelligent data management can help you achieve greater ROI and socialize and share insights with all stakeholders in your organization. With real visibility and knowledge, everyone can better understand the nature of the data they interact with every day.

Adrian Knapp is the CEO and founder of Devices.