Data as a Service: 5 Strategies to Transition How You Access Data

Data as a Service

Information wants to be free — at least that’s the saying. And like any good saying, you can read it in one of two ways.

First, information seeks to be out there and open to all. Second, it doesn’t want to cost a thing. No matter how you see it, either interpretation leads to the idea that data should be available on demand, which is how data as a service was born.

At my previous company, we brought the concept of DaaS to market by asking ourselves, “What’s more valuable? The data container or the data itself?” While the container has value, it’s worthless without good data, so we gave customers full access to our data for a monthly fee.

But with the increase in data availability, DaaS evolved. It was no longer enough to provide data access. You also had to analyze it and slice it up into easily digestible nuggets. In other words, it only has value when it’s tied to the ability to act.

The Silver Lining

When you move to DaaS, you no longer have to procure and manage data sets. What’s more, your entire team can access a single source of data from anywhere at any time. Throw in the cloud, and you bring costs way down — and that will be the future of DaaS.

Think about it: Companies spend tremendous amounts of money building state-of-the-art infrastructures, but they don’t have the necessary data to run them. The cloud makes data always accessible.

What’s more, most companies silo their data. It lives in multiple places, making it difficult to share information from one department to the next. If they put all that data in one place and created a single source of truth, the whole company can now work from the same knowledge base.

Getting all that data onto the cloud helps eliminate one of the biggest rate-limiting factors in business: decision-making. All thing being equal, access to quality and trustworthy information allows you to make faster, more informed decisions.

Make the Move

So the question remains: How do you go about making the transition to a new way of accessing data? The following can help:

1. Don’t get fancy. Go through the same process as converting from software to cloud. The biggest difference is that you’ll want a single source of truth with data as opposed to multiple different software applications. This isn’t to say you won’t have multiple data sets, but they’ll fall under one master data management system.

2. Automate everything. Moving data by hand doesn’t work. Tie together all the disparate data by automating its movement from its multiple sources into your API. Because this is more than just a file transfer, you may need to outsource the setup — unless, of course, someone in-house has API integration expertise.

3. Put up data barriers. You can prevent at least one of the killer D’s of data (duplicate, dirty, dead) by putting de-duping at the forefront of your data Management Strategy. Using a business’s primary URL, for example, can often prevent duplicate records at the door to your system.

4. Implement the 80/20 rule. Don’t wait to implement until your data is flawless — there’s no such thing. Instead, get the data 80 percent right by putting in 20 percent of your effort, and then work on its quality as you go along. You may be afraid to move to DaaS, but the downside of switching is no worse than the current state.

5. Do it as early as possible. Going from one system to another is tough. Be proactive about the process so you can stay competitive. If a company deals with compliance regulations, there’s an added risk, which can complicate the transition. Get in front of it, and commit to a plan. Dragging your feet can lead to a loss in market share.

In all honesty, there’s no easy way to switch. Although moving to the cloud isn’t possible for all businesses, it does provide a competitive advantage — especially with the speed at which data changes. After all, business goes by a law of change or die, and those that can’t keep up with the times get displaced by those that can.

By Jim Fowler, Founder and CEO of Owler.

Steve Prentice

Episode 4: The Power of Regulatory Compliant Cloud: A European Case Study

An interview with Johan Christenson, CEO of CityNetwork With the world focusing on the big three hyperscalers, there is still room – and much necessity ...
Kaylamatthews

What Amazon’s Kendra Means for the AI and Machine Learning Future

Amazon's Kendra Learning Future Most people feel a bit astounded when they type a query into Google and get relevant results in milliseconds. They're probably ...
Mark Barrenechea

Information is at the Heart of Your Business

Information Business Even though digital information is evolving at a rapid pace, the world is still document-centric. Documents, whether created by a human or generated ...
Thomas Franklin

Future of Stock Markets : Raising Capital Through ICO is 10x cheaper and 20x easier

Future of Stock Markets: Raising Capital Through ICO How blockchain will replace the stock markets as we know them today. Welcome to the future. It’s ...
Machine

Machine Learning: The Importance of Actionable Data

The Importance of Actionable Data How awesome would it be to know for sure exactly what your customers want to see from your business? Imagine ...