Businesses struggle daily to stitch together the data they need to make effective decisions. Point solutions put in place over time for finance, HR, sales, marketing, and IT needs were never intended to report their data alongside data from other applications. For the most part, they’re siloed systems, with siloed data. And that makes for uninformed and delayed decision making.
Seems nonsensical, right? If you built a new business today and thought about analytic needs upfront, you’d know you need an overarching data strategy to ensure that—as data from different applications comes in—you can easily integrate and analyze it together. How else will you have a 360-degree view of operations, opportunities, and challenges?
But businesses bought—and in many cases, still buy—systems for what they do, not based on how easy it is to report on the data. After all, analytics only has emerged as a core business requirement within the last 15-20 years. And for the last 15-20 years, buyers—many of whom skewed toward short-term budget savings versus long-term business benefits—were promised fast, ad-hoc, self-service analysis; pre-packaged, relevant content; business-driven logic; and a safe environment in which business users could conduct real analysis. Unfortunately, those promises remain unfulfilled.
Instead, businesses take on a haphazard, painful approach to try to muddle through the analytics mess they created for themselves. They spend a significant amount of time and money trying to integrate data from multiple systems—usually via an expensive, time-consuming data warehouse and data cubes—hoping the resulting data is correct. They implement separate visualization tools, reporting tools, database structures, and new processes to try to blend siloed data into usable information. Yet they still suffer from data latency and data fidelity (transaction-level access) issues: data looked at today was pulled days—or even weeks—ago, and data is lost while building structures for business analysis. Even after all this work, these structures never really perform as promised.
Much like a second story on a house, if you don’t plan for it ahead of time, you’ll have to completely rebuild the foundation to support any new needs. It’s much better to plan for analytics—for that second story—from the very beginning and weigh all decisions with that end goal in mind. At the same time, you need to build an analytics foundation flexible enough to quickly accommodate users’ future needs. That’s a tall order, one previously unable to be fulfilled.
What they lack is a purpose-built platform for data access and analysis in a self-service paradigm. A platform that delivers business value day in and day out, and empowers non-technical business users to ask questions and run reports.
Even popular analytics platforms such as Cognos and Domo make it difficult, if not impossible, to achieve this near-real time, self-service goal. Going back to our construction analogy—if you decide to add a window to a load-bearing wall in your house, cutting a hole for that window may make the wall structurally unsound. So you either have to spend a hefty sum to make it work or install the window elsewhere.
Attempting to stitch together applications after the fact for analytics purposes is very much the same scenario—even if it’s possible, what it takes to get there likely is not practical.
Adding to the confusion are sexy visualization tools such as Tableau that make the transformation of legacy analytics look easy. But the reality is, adding a visualization tool to siloed data is not a quick fix for—or a fast track to—analytics, and it certainly isn’t cheap. It takes an enormous amount of work and a substantial amount of money to put in place behind any visualization tool the structure needed to flow accurate data from multiple systems through it while empowering the tool’s users with self-service analytics. In fact, I often see a multiple of 50 to be quite common when attaching a visualization tool to legacy data and analytics applications: if you spend $10,000 on a front-end visualization tool, expect to spend an additional $500,000 in consulting services to get it to operate the way you need it to work.
Even those companies whose data integration efforts succeed quickly realize the legacy tools they have in place aren’t designed to help them have a “conversation” with their data. And that’s exactly what you need in today’s self-service world.
For example, you might design an initial report to answer 20 pre-defined questions, but now you need to answer 24. You’re essentially stuck, and you’ll need to involve IT or a data scientist to re-write reports for you. By the time you do answer those new questions, they’re no longer as relevant as the five new questions that popped up since then.
This is what I mean by having a conversation with your data—what’s discussed and what’s needed shifts frequently and unexpectedly, and you and your data need to be able to respond and follow along.
This brings me to what we at Incorta do and why it makes us BADASS.
Many tools or structures claim to be self-service and ad hoc. Some of them even deliver content or allow for business logic. Others claim performance gains and provide some operational transactional analysis. But it’s not one capability—or even two or three—that gives users what they want. It’s the combination of all of these capabilities, within a single platform.
And that’s what Incorta—and only Incorta—does.
Incorta is a “Business Analytic Database Augmented for Self Service.” That’s a mouthful, so we simply think of it as “BADASS.” With it, we’re changing the way companies buy, implement, and leverage business analytics.
That’s because we don’t want asking the questions you need answered to be difficult. We don’t want to slow you down. We don’t want you to have to rebuild your entire data model whenever you want to change the questions you ask. We don’t want you to have to choose between data granularity or speed. And we don’t want you to have to constantly wait to get what you need.
We understand you’re never done with any type of analysis; instead, you constantly iterate on it. That’s why Incorta lets you and every other user have that conversation with your data—in fact, we even encourage it. When one insight leads to another, you can go with it. The more you know, the more you want to know, and—with Incorta—the more you can know. With Incorta, you can work with the data, unworried if the question you need to answer was considered when the model was originally built.
In essence, Incorta is the epitome of self-service analytics.
Here’s how we do it.
- Our unique Direct Data MappingTM engine handles data in its original shape, eliminating the need for complex ETL and allowing you to deploy cost-efficient analytic solutions in only days.
- Our technology is “data relationship-aware:” as we pull data into the Direct Data Mapping engine, it’s automatically mapped to other data—you don’t need to preconceive dimensions or drill paths, nor remodel the data for different analysis later. With Incorta, no roads are required—you don’t have to pre-plan your route.
- For more traditional analytics needs, we provide pre-built applications for Accounts Payable, Accounts Receivable, Financial Assets, Inventory Analysis, Enterprise Assets, Sub-Ledger Events, Purchase Orders, and Value Chain Planning that accelerate deployment and minimize the cost of ongoing maintenance.
- With Incorta, you don’t have to wait for your data. Our one-of-a-kind technology can process hundreds of millions of rows of data (from transaction to aggregate) and return results in less than a second! A mere five-minute latency on data refresh exceeds the needs of most organizations, ensuring businesses easily leverage the up-to-date information they need to make decisions and react quickly to changing market trends.
Organizations accustomed to traditional analytics are awestruck by what we help them do. They know legacy analytics approaches were designed for efficient storage—not answering real-time business questions—are expensive, and allow less freedom.
Incorta, on the other hand, bridges the gap between IT standards and business needs. That’s why we consistently see Incorta implementations go live only six weeks after software acquisition (using only internal resources); cost 10-20X less to implement and maintain than standard, data warehouse-driven approaches; and generate queries 100X (or more) faster than solutions such as Exadata, Redshift, and Vertica. It’s why we believe Incorta is the world’s most agile business analytics database.
Take premier point-of-sale provider and Incorta customer Toast, for example. Toast helps thousands of restaurants increase sales and develop smart front-of-house and back-of-house processes. Internally, Toast relies on Incorta’s data analysis capabilities to streamline internal processes and drive increased revenue. From sales pipeline to general ledger transactions—and every step in between—Incorta is the bridge that delivers structures and ad-hoc analysis to Toast’s business community. Instead of moving data from system to system and trying to stitch it together, Incorta delivers the information Toast users need (from transaction to aggregate) for effective decision making. With Incorta, Toast’s business community no longer spends time collecting data—they spend time using it.
“Incorta lets us more quickly fine-tune our business strategy, which ultimately increases revenue. Before, it could take weeks to sort out all the noise when we needed to get a handle on our previous month’s performance. Now, we know in real time what’s going well and what isn’t. It’s incredible to have that kind of information at our fingertips.”
—Tim Barash, CFO at Toast
Thanks to Incorta, any business can be like Toast. With Incorta, you can go places with your data you couldn’t travel to before. You don’t need to spend years planning and building, and it doesn’t have to take a long time to get there.
This is the new world of BADASS analytics. We’re proud to pioneer it.
Want to learn more about why Incorta is BADASS? Contact me directly at firstname.lastname@example.org.