Are you facing pressure to make better decisions, faster? Are you uneasy about making too many gut-level business decisions? Are you being asked to have a data strategy from above and wondering how to compete in a data-driven world?
You are not alone. These are common themes emerging in today’s digital economy. Customers of all kinds – from consumers to enterprise businesses – have greater and greater choices than ever before. That means your customers are demanding more service, faster, and at a higher quality. How you decide to meet these needs is becoming very complex. You need to choose among many competing options. Increasingly, making these decisions by trusting your gut is a recipe for disaster!
These difficult decisions are not made any easier with the rise of Software as a Service (SaaS). While it’s easy to get up and going with SaaS offerings to handle business productivity needs, with every new SaaS offering you use, you end up silo-ing your data even more. Every department, every business function, has multiple data silos that make holistic business analysis an uphill climb. How can you tie together customer satisfaction and operations data, if the data is in two different systems?
Can you find the data you need? Once you find it, do you trust it? It just shouldn’t be this hard to make business decisions!
We know this is a common problem, because we hear it over and over again from our customers. We continue to hear about this problem, despite the relative maturity of “big data” systems. If big data has been a thing for at least two decades, why are we still struggling to make sense of it all? Our diagnosis is pretty simple:
- Data projects that lack a business goal will fail, and most data projects lack a clear business goal, such as “increasing customer satisfaction.”
- It’s hard to find people to do the hard work of connecting systems and pulling data out.
So, despite fantastic big data ecosystems being widely available, if you lack a clear business objective and you can’t assign people to roll up their sleeves and move data to where it needs to be, then unfortunately your data initiative will die on the vine.
Our solution to this is very straightforward:
- We start with the business goal and never put it on the back burner. Our consultants are trained to listen for and capture business objectives from your team (and people around your team) and hang onto them tightly, while allowing flexibility when it comes to the implementation details. This is very rare in cloud consulting. Most cloud consultancies miss the business goals and skip straight to engineering. We think this is unacceptable and have seen it lead to purposeless, cash-hemorrhaging projects.
- We then rapidly get to work and implement our best-practices DataOps solution. It’s pre-built, uses 100% serverless AWS offerings, and is battle-tested over dozens of successful deployments and years of incorporating AWS best practices. Since it is serverless, scaling your DataOps foundation to dozens or hundreds of data sources is painless.
- Then, we connect your first several data sources, such as Salesforce, or logs, or customer data, or whatever we together have identified will support your business use case. This is the hard work of rolling up your sleeves, and we have the people to do it.
- Within the first two weeks, most customers are analyzing data from multiple sources in a single pane of glass.
- Finally, we make your analytics production-ready and help you share the good news around your organization.
These are the benefits that our customers have told us they have received.
- You can make better, data-driven decisions. Since we start and end the engagement with your business focus in mind, you are able to make better, data-informed decisions. Where before you were trusting your gut, now you have real, relevant, current data to support your decision making. You’re not driving blind.
- You can trust your dashboards and reports. Since we have implemented a best-practices Data Catalog, you have a crystal-clear picture of how your data got to its end state. You are not questioning “is this data real?” because you have clear traceability of data from source to metrics. If you can’t trust your data when you try to act on it, what’s the point?
- Your analysis gets even better with yet more data sources. Now that you have a central data lake with easy-to-replicate patterns for bringing in new data, you can make your analyses even richer by adding yet more sources. Many of our customers enrich their data with a wide variety of internal sources, and even external sources like weather and macroeconomic data, to find new correlations and trends that were not possible before.
- You feed a culture of DataOps. Word will get around that your team has the ability to drastically simplify data access and analysis because our DataOps Foundation comes with commonsense access rules right out of the box. It is not a threat to give access to the right people – it will help your business operate. This tends to have a flywheel effect. Other departments get excited and want to add their data; analyses get better and richer; then even more people want to bring in their data.
- You are now AI-ready. If all the analytical benefits were not enough, you are now also ready for AI and machine learning (ML). It’s just not possible to perform any kind of AI with messy data. With our DataOps Solution, you have solved two problems at once – you have action-ready business data, and you have cleared the path for repeatable AI projects.
You are not alone if you still can’t get the data you need. If your data still feels invisible to you, and you don’t think it should be so hard to crunch data for business outcomes, then you should know that there is a better way. Our DataOps Solution puts your business goals front and center. Our straightforward engagement has you centralizing and analyzing data, in the cloud, securely, within a week or two. Then, you can add more sources to your heart’s content and enjoy the benefits of being data-driven and AI-ready in today’s demanding economy.
To get started, contact us to book a discussion and a demo.
-Rob Whelan, Practice Manager, Data Engineering & Analytics
