What Is Data Management? How and Why to do Data Differently

Nowadays, there’s more data flying around online than ever. You can’t even go online without generating, encountering, or otherwise dabbling in data in some way – especially in business.

The right data can be worth its kilobyte-size in gold. Good data can serve as the backbone of business-critical operations; help organisations make clear and cogent decisions; and generally carry a business into a successful future.

So how well are you currently managing your data? Do you feel like your data is ruling you rather than the other way around? Feel like you’re just treading water in a deluge of spreadsheets and data points? It’s time for some data sanity. Let’s learn all about data management.

What is Data Management?

Data management refers to the practices an organisation uses to collect, organise, and process data. Good data management practices ensure that data is gathered, processed, stored, and protected in efficient, documented ways that strategically benefit the business: maintaining accuracy and accessibility; supporting analytical decision making; enabling seamless collaboration; upholding data privacy; and maximising data as an essential business asset.

A proper data management strategy formalises all of the above, whilst also providing important guidelines and rationale around your company’s use of data. Creating a data management strategy gives an organisation the opportunity to build their ideal data ecosystem from the ground up, in turn providing a complete, granular view of data use going forward. This strategy should also inform actionable, company-wide data and IT policies.

6 Reasons Why Data Management is Essential

Digging this deeply into how your company uses data may sound a little impractical – self-indulgent, even – but it really is worth it.

1. Data Has Value

Data is an essential IT asset that needs looking after like any other in order to keep your business trucking along. But just as any kind of asset can be stolen or tampered with, so can data. Hackers are always on the lookout for ways to extort money from businesses, hence why ransomware attacks (which effectively hold business-critical data to ransom) are at an all time high. Working out a strong data management strategy will help you keep your data assets well-secured and in prime condition so they can continue to serve you well.

2. Achieve a Top-Down View

When you establish what data your company has, you can work out exactly what information you can potentially extract, and if there are any gaps in that data that need filling to achieve your business goals. If you know there is a certain data point being measured, good data practice should tell you how it’s being collected, where to find it, and who has access.

3. Standardisation = Sanity

Armed with a bird’s-eye-view of your data practices, you can provide set, standardised ways of collecting, handling, and processing data; in turn building functional IT and data policies that enable collaboration, harmony, and clarity.

4. Accurate Data, Accurate Decisions

When you know for a fact that your data is as accurate as physically possible, you can make confident, impactful business decisions with both eyes open – and most likely plan for the future more effectively too.

5. Minimise Data Loss

When you know what data you have and where keeping it safe becomes much easier. A 360-degree view of your data can help you minimise losses of all kinds, from large-scale cyber attacks to simple questions of “Where the heck is that email?”. Knowing where your data is held and how it flows through your systems helps to inform effective cybersecurity and backup strategies.

6. Operational Agility

Having a concrete understanding of how your entire data ecosystem works is great for business agility. Knowing precisely how your company uses data can help you formulate a measured, informed response in the face of sudden market changes, team reshuffles, and IT challenges.

A Few Core Data Management Concepts

Data management is a complicated beast with a number of complex concepts lurking beneath the surface. Yet understanding these concepts is essential to understanding the full extent that a data management strategy can cover. Before we learn how to put your data management strategy together, let’s unpack some of these concepts – no dictionary required!

Data Collection

This one’s pretty simple: how are you going to collect data and store it in a secure way? How will your data collection methods uphold the integrity of the data and the data subjects’ privacy under relevant legislation like UK GDPR, CCPA, and APP? How will you keep that data secure as it moves around the wider internet and into/around your internal infrastructure (“in transit”)? How will you keep it secure when it’s simply in storage (“at rest”)?

Data Processing

Once you have your data, what are you going to do with it, how, and why? What software and storage will you need? How will your organisation’s numerous departments/functions use and collaborate with this data? How well does data generally flow around your organisation - do you have some data silos you need to break down first? Also, what legal grounds do you have for processing your data in line with privacy legislation?

Data Governance

Nobody can make meaningful, confident decisions with incorrect or incomplete data. Therefore, maintaining data integrity – the data’s accuracy, consistency, and completeness – is essential in business. Data integrity can also touch upon the physical integrity of data storage, access, and use. Data stewardship is a related concept that covers the data’s fitness for purpose; prevention of unauthorised access; as well as practices like data enrichment, cleansing, and purging. The umbrella term, data governance, can also involve making sure that data is kept ethically, and in a valid, usable format.

Data Security, Protection & Privacy

With cybercrime on the rise, data security and privacy is of utmost importance. Organisations should therefore:

How to Create a Data Management Strategy from Scratch in 6 Simple Steps

1. What’s Your End Goal?

Before you make any further decisions, you need to nail down what you want to achieve with data. What are your business objectives and reasons for change? What sort of data functionality do your team need to operate? What kind of reports do you want to run? What kind of metrics do you want to keep an eye on? How will you and your team interact with data on a day-to-day basis?

Seek cross-departmental buy-in right at the start of your journey – especially if the data and processes you intend to build will affect or adjoin other departmental functionalities. Research thoroughly to make sure your data restructuring plans that don’t don’t mess up a critical data flow or generally make anyone’s lives more difficult.

Not doing so may create roadblocks for people, possibly leading them to seek their own solutions. These ad hoc solutions can lead to issues like insecure data usage, data silos, SaaS bloat, and shadow IT – basically the polar opposite of what you’re trying to achieve!

2. What Data Do You Need?

You could consider this the “million dollar question”. In order to carry out the functionality you require, what data points will you need to collect? What data are you currently collecting and how does that stack up to your plans?

This exercise isn’t about hoarding as much data as possible. It’s about rationalising what data is just enough to satisfy requirements. Only collect data points if you have a watertight reason for doing so, especially if it relates to personally identifiable information. The more data you have, the more value you stand to lose in the event of a technical hiccup or a cyber breach – and the more explaining you’ll have to do to data regulators!

3. What Processes Will You Need?

Now you need to think about what processes you need to put in place for your teams to be able to carry out their roles using the data. What departments will be interacting with the data? Will they need to amend the data, add to it, or simply read it? What will be needed to pull data from the right places and put it into the processes and reports you need? What processes are required to generate new data, or cleanse/purge old data that is no longer useful? Do you need to synchronize data between different databases, for example, MongoDB and PostgreSQL?

Now, take a look at the processes you already have in place. Would changing things just be a case of collecting another data field or sharing an existing data point with another role or department? There’s no point completely reinventing the wheel if you can simply tweak something you already do.

You might find it useful to draw out two data flow diagrams. The first to represent what you’re doing now, the second to establish what your ideal data flow needs to look like. Where are the diagrams similar? Where are they different? This is a handy visual way of uncovering what needs to change and what needs to stay the same.

4. What Technology Will You Need?

With your data points and processes decided, it’s time to explore your tech options. What software and storage solutions will you need to do what is needed? How well are your existing solutions serving you? Will you need new or upgraded solutions given your renewed data needs? Are there any single points of failure in your current systems, or any places where your team has to manually bridge a gap between two tools or functionalities? Re-addressing your data needs is a great opportunity to look around at the market and seek fresh, better options.

There are effectively three parts to this equation – three S’s: Software, Storage, and Security. Software is probably the most straightforward – choosing a tool that will allow you to do whatever you need to do with your data.

Storage however can depend heavily on functionality. Sometimes – as with CRMs like ours – data storage may be taken care of within the software solution itself. Other times, external cloud storage from the likes of Google Cloud or Microsoft Azure might be more appropriate. If you’re dealing with particularly sensitive data, you may want to keep your storage in-house on internal servers. And don’t forget backups!

Cyber- and network security is an essential consideration for any organisation nowadays, regardless of the data they hold. Consider how you are going to secure your data both at rest and in transit. Work out how you’re going to protect your organisation from things like credential theft and social engineering. And on that note…

5. Who Will Be Responsible for Your Data?

Data is a powerful resource – and as we know, with great power comes great responsibility. So who is going to be responsible for maintaining high standards of data accuracy and fitness for purpose? Who is going to manage the security of the data and keep it safe from misuse? Who is going to be responsible for dealing with privacy requests from data subjects?

Tasking a responsible member of your team with data compliance matters can keep your data under control and assist in compliance with crucial data privacy legislation like GDPR, HIPAA, and APP.

6. How Will Your New Data System Be Rolled Out?

You’ve made all of the important, highfalutin decisions – so how are you going to execute them? Will any new software, storage, or security measures need to be implemented? Will you be able to blend your old way of doing things into your new systems, or will you need a concrete switchover date? What data will need to be transferred over to new systems and how?

Will your team need retraining in order to use the new systems? How are you intending to get buy-in from those who will need to use the new system – how will the new way make their lives easier? Will any new data habits need to be formed relating to functionality or security?

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Our intuitive yet powerful CRM is designed especially for small to medium enterprises who strive to build long-lasting client relationships through outreach, collaboration, and data. Make the most of our no-obligation 14-day free trial – register today!