May 05, 2017 · by: Matthew Halliday · Blog
Data Warehouse Replacement ,
Star Schema ,
Data Warehousing: A Competitive Disadvantage!
It’s a fact. Most companies today use a data warehouse. Frankly, they didn’t have much choice—they needed to be able to ask daily questions of their transactional data that required performance and scale currently impossible using a traditional relational database. And historically, the only way to do that was via a data warehouse.
Maybe you were one of them. You likely knew the negative side effects with a data-warehouse approach—having to pre-aggregate data, develop and maintain complex Extract Transform and Load (ETL) processes and trying to rebuild original security settings as best as possible. Relative to the demands of the business in today's data driven economy, this traditional approach has become a competitive disadvantage.
I hate to be the bearer of bad news. But—rather than enabling analytics—your data warehouse is actually killing the very insight your company needs to remain competitive.
Here are the top three reasons why.
Overly time-consuming. Data in a data warehouse exists in a different shape and form than original data living in your source systems. Once you’ve launched your data warehouse, you still need to update and maintain it to try to keep pace with your business needs, which constantly evolve. To make any changes—even simple ones like adding a table or an attribute to a table—you need to involve analytics experts and your IT team. And this change process can take days, weeks or even months, depending on what needs to be done.
Fruitless busyness. Every company needs a competitive advantage in today’s market. You can bet that if you don’t have it, your competitor will. So it’s logical to believe a data warehouse would be a foundational part of a core competitive strategy, given the dollar and time investment so many companies make in them. Yet data warehouses more often than not put you at a competitive disadvantage because it requires so much work to maintain them and update even the most basic reports.
It’s ironic, actually—companies invest in expensive data warehouse projects to gain deep insight, yet few ever achieve that goal due to the work required to get there. Much of this is because analysts using data warehouses spend most of their time working on basic reports—they rarely have the chance to go beyond that. And even if they do, there are limits. For example, you can’t easily run machine learning algorithms if you’re using a data warehouse.
But the biggest way data warehouses are killing your analytics is because of their inherent inflexibility. When building a data warehouse, you need to know the questions you want to ask before you design the solution. Just imagine if your social interactions were like that. You have to write down all your questions before you meet with someone. No follow up questions unless you anticipated those. And then you have to rework the solution if the questions you want to ask change, which they invariably will.
After all, the whole purpose of analytics is to discover insights. An insight by definition is “an understanding of relationships that sheds light on or helps solve a problem.” It’s something you probably didn’t think about before. And insights tend to multiply—they generate new questions you want to answer, questions you inherently couldn’t anticipate.
That’s why I believe data warehouses are now a thing of the past. An archaic relic that misses the mark when it comes to today’s analytic needs.
And this is why I’m so excited to work at Incorta.
Incorta transforms the whole relationship between people and their business data. We fundamentally change the way companies implement analytics—bypassing data warehouses altogether—so users can get the true, real-time insight they need.
With Incorta, IT creates secure frameworks in which users can engage with unlimited amounts of data while using their existing, favorite tool. No one has to pre-define the questions. Now, users can actually have that conversation with their data—quickly answering the most pressing questions (without having to know what they are ahead of time) and also answer any new ones that come up—all on their own, without needing help from IT or data scientists.
Here are a few real-world examples of what Incorta customers can accomplish:
· During a two-hour proof-of-concept with Incorta, a top 10 university easily utilized the Incorta platform to analyze their data and build an insightful dashboard. Additionally, they were easily able to locate and fix a data mistake that had unknowingly plagued them for six months.
· In less than a day, the Incorta team built a comprehensive and interactive dashboard for semiconductor giant Broadcom that would’ve taken Broadcom’s team six months to build themselves using existing technology. Additionally, the dashboards Incorta built were much more flexible than what Broadcom could’ve achieved before.
· Incorta helped one of the top three consumer electronics companies in the world simplify their analytics infrastructure to minimize data errors caused by risky, complicated data pathways.
Despite a world that constantly changes, nothing can be done “on-the-fly” when working with a data warehouse. The resulting busyness may mean job security for some, but it eats up valuable time and resources that could be leveraged to create true differentiation.
Today, you have a better option for gaining the secure insight you need. An option that more quickly, securely analyzes complex data from multiple sources, without degrading system performance. An option that encourage a user’s curiosity and investigative nature.
That option is Incorta.
Want to learn more about Incorta’s real-time, no-data-warehouse analytics technology? Contact me directly at firstname.lastname@example.org or @layereddelay.