How a data warehouse can help organizations democratize data

Data democratization allows everyone in your business, regardless of their role or level of technical savvy, to access and use data as it relates to their role. A self-serve data model from a single source of truth is essential if you truly want to make your data work for you. It gives the right people access to real-time or near real-time information necessary to be competitive, and when done right, it unifies the company across various departments or locations.

Democratizing your data is particularly advantageous in two scenarios:

1. Your business is spread out geographically, meaning data input and/or use come from various access points — common if you have a sales force, work in certain industries like logistics, or operate multiple branches.
2. You’re overwhelmed as a data analyst or CDO but need your department to run lean, which is often the case with startups and small businesses or companies in the process of scaling.

While everyone wants data democratization these days, it’s easier said than done. Some common hurdles, like outdated processes and perceived budget constraints, make it difficult to achieve. But it’s not impossible if you utilize a data warehouse as part of your plan.

Common Challenges in Creating Sustainable Data Systems

Data governance issues

Arguably the greatest concern in building a data system that a business can actually leverage is data governance. This includes a range of elements, such as:

• Internal data security
• Compliance with larger data policies
• Data accessibility and availability
• Data workflows

How do you know if you’re having data governance issues? Beyond security breaches or risky violations, poor data quality (see more below) and excessive limitations on data access are the calling cards to watch for. With the latter, you’ll see requests for data that rapidly exceed your small department’s ability to provide them, resulting in staff burnout (or your own overwhelmed status) or employees operating in a less timely and efficacious manner.

It’s a rule of thumb that businesses should have their data governance concerns ironed out before implementing data democratization. You’ve probably heard the saying, “With great power comes great responsibility.” Such is the case with democratizing your data. Once you allow easier access, you also increase the risk of data breaches or regulatory violations.

Therefore, you need to understand in advance where these problems are likely to occur and head them off at the pass, so to speak. Develop policies about access, data sharing, information communication, and the like to prevent legal or ethical risks later. These include:

• Password strength and protection
• Encryption of communications involving sensitive data
• Obtaining permission when using certain third-party data (like from customers)
• Educating employees on phishing and other data theft scams
• Using only certain computers or devices to work with the most sensitive data
• Developing bring-your-own-device policies for workers using their own laptops or phones
• Ensuring third-party business integrations offer the necessary security when working with your data
• Limiting access to those who need information, not necessarily the entire company

The point of data democratization is to make data more useful and simpler to obtain; it’s not to create a free-for-all where anyone can access every bit of information.

Understanding what to do with data

Having a lot of data at everyone’s fingertips can be great, but it’s only as good as each worker’s knowledge of how to find and apply it. It’s not unusual for employees to need coding to access usable data, but that isn’t realistic in most situations. Educating data users within the framework of what they need under the umbrella of data governance is vital.

For example, say you have a sales department that is spread across the United States. Giving them a vast trove of client and accounting data and asking them to use it wastes their time and risks getting into the data governance issues mentioned above. Instead, sorting it by geography (territory), item sold, or sales rep makes more sense. But reps may also need to share data between themselves or with other business departments.

You need to make the information more usable, especially if it can be sorted by different criteria based on a sales rep’s needs at the moment. They may want to see who their biggest purchasers are launching a new product. Conversely, they may wish to sort by smallest purchasers if looking to expand and top customers are already maxed out. They may want data from a different territory if looking for similar clients where colleagues have successfully boosted sales. There are alternatives, like dynamic dashboards, to help with this that don’t involve brittle spreadsheets and siloed data (see more on data fragmentation below).

Data quality

A related issue is poor-quality data resulting from a host of challenges, including accessibility, arduous transformation processes, and outdated information. This can cause a spectrum of troubles ranging from employee frustration to actual business harm. An employee might have the wrong information about a client’s past invoices (merely embarrassing). Or a board member could share erroneous information that results in a liability claim against the company (high risk).

This is another case for reasonably limiting access to data with good data governance at the start. More data isn’t always better. Better data is better. This means your business has to examine:

• How data is collected and the reliability of sources
• How long data is stored and how often it is updated
• How data is sorted and manipulated for use
• How internal users can add to the data pool when relevant
• How data can potentially become corrupted
• How old data is removed and destroyed
• How systems review and protect information for public sharing

Fragmented or siloed data

As more and more work is being performed online, remotely, and globally, data is increasingly broken into silos or chunks that must be integrated before it can be used. This used to be a problem limited to enterprise-level companies, especially those with widely distributed sales departments, but today it’s a growing obstacle even for small businesses.

A simple example is an e-commerce company that has inventory at a main warehouse in the US and a fulfillment center overseas. If the fulfillment center is not sharing the right data with headquarters, the business won’t know when to ship more merchandise abroad to complete orders in a timely way. When it comes to reporting, the main office will need sales and overhead data from its foreign center as well. So, the two cannot have siloed data but must be interconnected.

Cost restrictions

It can be cost-prohibitive for businesses to implement the data systems they really need. So what happens? They limp along making do, falling further behind in their data goals with every passing year.

It’s best to see data improvements like democratization as investments. Yes, there is an up-front cost. But when done right, data democratization should help businesses realize more profits over the long term.

If cost makes sweeping data changes prohibitive, start with one department first. Make the necessary changes, and then move on to the next department. Set up a timeline and budget to do this, lest you revert to “someday” thinking where nothing really gets done.

C-suite buy-in

One reason money isn’t always allocated where it should be for data solutions is the lack of buy-in up in the C-suite. Executives may not comprehend the need for better data systems or may be focused on short-term financial gains over investing in data strategies that pay off over the long term. It becomes a chicken-egg situation where the longer you put off fixing holes in your data, the more expensive it becomes… so people at the top dig their heels in even more.

To get the universal buy-in you want, it’s best to lay everything out for executives to see. Show them how data problems are affecting the company’s bottom line. If staff turnover or recruiting are issues, such as with overloaded IT employees, tell them about that. Are sales reps grumbling about not having the necessary tools to do their jobs? Enlist them in your campaign to bring data systems up to date.

Outmoded methods

What happens when cost restrictions and lack of C-suite support meet? Your data systems become outdated. Are you using brittle spreadsheets that require egregious amounts of manpower to manage your international supply chain or inventory? Are data analytics shoved under the IT department rather than given their proper place in the company? It’s time to level up.

How Data Warehouses Work

A data warehouse might be the answer you’re looking for. A data warehouse is a central repository for all the information your business needs to run and grow. It consolidates data from all your sources to get better, faster insights and make more informed decisions for your business. You get a single source of truth for your data, which improves accuracy, speed, and agility with data analytics and applications. This centralized hub enables the people in your organization to access the data they need when needed — democratizing your business data to eliminate the system challenges listed above.

Unlike a data lake, which stores data in a more raw form, a data warehouse stores relational data in a more structured or curated way. It can contain multiple databases or data marts used by people in specific roles in your company, like sales reps or inventory managers. Back in the 1980s, data warehouses were typically on-premise in mainframe computers. Now with the security and convenience of cloud data warehousing, setting up and maintaining a data warehouse is faster, easier, and less expensive.

Choosing the right data warehouse brings your business a wealth of benefits, including:

• Scalability to grow with the business
• Improved decision-making capability
• Separate transactional databases and data analytics
• Better data quality with greater usability

A managed data warehouse like Panoply gives you all that and more:

• Low-to-no code ELT connectors
• In-platform visualizations for quick insights
• A workbench to explore your data in SQL
• A single source of truth for data from all your sources

The end result is freer-flowing data that benefits everyone in the business — and that’s really the definition of data democratization.

Panoply’s platform enables users throughout your business to sync, store, access, and visualize their data in just a few clicks. As a managed ELT plus data warehouse, Panoply makes it easy to combine and query data from all your sources and get quick visualizations in-platform. If you want to see how democratizing data can bring more value to your business, let’s start the conversation. You can request a demo and free consultation to see how Panoply can help your business democratize its data.