April 20, 2017 · by: Bill Witte · Blog
Direct Data Mapping ,
The New Enterprise Analytics: Top 4 Ways Speed Matters
We’re all awed by raw speed. Fast athletes, fast cars, fast anything… fast is good; faster is better.
When it comes to enterprise analytics, this focus on speed isn’t just an obsession—it’s a necessity. In fiercely competitive markets where insightful data can launch you beyond your competitors (or lack thereof can drag you behind them…), you need analytics that provide near instant insights into your business. But in an age where fast analytics is assumed as a given, what does fast really mean anymore?
Most people equate analytic speed with how quickly they can return queries during analysis. That’s important, for sure, but it’s a narrow view of what you need in a true enterprise analytics platform. This focus likely arose honestly from the paralyzing effect of growing data volumes and complexity; the larger your data sets and the more join-intensive, the more difficult it became to analyze. For this reason, before you could analyze complex data, you had to build a data warehouse—a costly, time-consuming process that really never ended. In the past, data warehouses were the only way to get to some semblance of analytics, so we all gritted our teeth and bore the pain.
But I’m happy to report the time has come to re-think this cumbersome, expensive, infrastructure-intensive approach. A new approach for enterprise analytics bypasses the data warehouse, arriving at insights much, much faster. It gives you what you’ve wanted all along: real-time insight into how your business operates, so you quickly can make informed decisions that improve your bottom line.
In this new way of thinking—this new, modern paradigm—you measure analytics speed by more than just query time. Here’s what to look for:
1. Time required to roll out an enterprise platform for analyzing complex data. Many business analysts focus on the front-end—how to manipulate and visualize the data they already can access. But the real heavy lifting and time delays caused by legacy enterprise analytics occur during analytics development, set up and deployment—heavy lifting and delays eliminated by modern enterprise analytics like Incorta.
New analytics platforms such as these vastly speed the development of secure analytic applications—reducing the time required from months to only days—by eliminating the need to build data manipulation infrastructure and eliminating costly, error-prone processes. You don’t need to pre-aggregate data anymore, so data warehouses become obsolete. You also don’t need to rebuild security, so your data remains secure and compliant at all times (next-gen analytics inherit already-vetted security settings from the source applications). And it’s easy to access and integrate disparate data sources, with virtually no data prep needed.
2. Time required to gain self-service insight. Self-service insight is virtually unheard of with legacy analytics platforms; instead business users must rely on IT to build reports and dashboards to tap into their organization’s business data. Non-technical business users want and need direct access to the data and want to be able to manipulate it through easy-to-understand, intuitive means.
Incorta embraces modern approaches to analytics that make self-service possible, and let business users easily explore and derive insights from their data. Incorta’s Google-like search capabilities let users search on business terms (and not table names) to discover the data they want to analyze. Also, direct integrations with Excel and Tableau empower business users to easily, securely explore their enterprise data in real-time without requiring IT to pre-build reports.
3. Time required to add a new data source. The never-ending nature of analytics results from the cold, hard fact that you’re never truly done with any type of analysis. You constantly iterate on it—one insight leads to another question, causing you to ask yet another question of your data. Yet working in the static, rigid environments created by a data warehouse-driven approach makes it difficult for a business user to ask subsequent questions. As soon as you ask a question that requires an additional data source, you need to involve your IT team to rebuild the whole data model, and that takes time. So you’re constantly waiting to get what you need while your IT team rebuilds the data model.
Since modern enterprise analytics eliminates the need to pre-aggregate data—and in doing so, eliminates the need for a data warehouse— you very quickly can add a new data source and get back to your analysis, gaining more and more insight into how your business works.
4. Time required to make decisions based on analysis. Business data changes constantly. Each transaction completed, each order booked and each inventory item depleted are recorded in your business systems constantly. As the real-time changes to your systems occur, so, too, do changes to analysis of the data. Yet, when data is housed in a traditional data warehouse, it typically updates in batch jobs that occur overnight, so the data you’re analyzing is often 12-24 hours out of date.
Modern enterprise analytics access data directly from the source systems as frequently as 4-5 times per hour. This may not be true “real-time,” but tapping into data that is no more than 15 minutes old unveils a whole new level of understanding of one’s business, allowing for the acceleration of decision making—something just not possible when looking at day-old data.
Proof Points for You Skeptics
Most people today still believe they need large data infrastructures and data warehouses to understand their complex data. That’s just not the case anymore. But real-world data and comments from Incorta customers justify it better than I can:
“In just one hour, we were able to load and analyze the data from millions of transactions—and see some new insights.”
- Central IT Technical Manager for a Top 10 University.
“Business users are blown away with how fast we can actually understand them and come back with a solution to them. They have never seen something like this before—the IT team being this responsive to meet their needs.”
— Ajit Oak, Sr. Manager of Business Intelligence for Broadcom.
“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 for Toast.
You use analytics and insights to make decisions about your business. The more quickly you can access them—and the more accurate they are—the more agile you and your business can be. It’s time to try modern enterprise analytics. It’s time for you to be the fastest one, for you to be “that kid.”
Skeptical? I welcome the opportunity to show you first-hand how Incorta’s no-data-warehouse platform works. Contact me directly at firstname.lastname@example.org.