Discover PerformanceHP Software's community for IT leaders // March 2013
Start a conversation with your data
Business moves too quickly to wait hours for incomplete reports. The next level of analytics puts you in immediate, interactive dialogue with your data.
Your old way of finding what you need to know doesn’t work anymore. A data warehouse simply can’t create meaningful business intelligence (BI) from big data—not at the speed that today’s organizations demand. The future normal for enterprise BI is a conversation with data. In a conversation, questions are answered promptly, and each answer provokes new ideas that influence the dialogue.
Many organizations will have trouble adjusting their data management culture for a more responsive age. Ironically, this transition may be most difficult for those with years of in-house data management experience.
Success means overturning much of what your organization already knows to embrace new ideas about data analytics.
Why data needs to talk
Given a finite amount of data and an overnight window for processing, data warehouses do a reasonable job of delivering BI. A needle in a haystack isn’t so hard to find if the whole haystack is in a data warehouse. But when you’re searching a sprawling field of fresh-cut hay—perhaps searching not just for a single needle but patterns of them—you need a new approach. For data, it’s the ability to ask follow-up questions to refine the results that your data gives you.
As lines of business seek faster, better intelligence, executives and business analysts will want to invent new data queries on the fly, receive an answer within seconds (not hours or days), and then use the answer to formulate the next query. Faster, better answers increase business success by making you more responsive to customer needs and trends, and by letting you innovate faster than your competitors. Organizations that can’t converse with their data will quickly lose ground to competitors who can.
Cardlytics, which delivers targeted advertising messages to 200 million financial services customers, found that highly responsive analytics tools make a real difference. “Now that we can get our answers back quickly, it allows us to start exploring again and have that conversation with the data,” says Jon Wren, who as director of data innovation for Cardlytics helped implement the analytics solution.
The Atlanta-based company replaced its aging analytics system with Vertica’s advanced, high-speed, high-capacity analytics platform. The resulting ability to converse with data improved the core business and reinvigorated the operations team by letting them really dig into data to find opportunities to innovate.
Wren says that conversing with the data also helped Cardlytics be more efficient and profitable by delivering better ads at a local level. “Now we can get even more targeted for our customers,” he says. “We’re not forced to focus just on the big, national offers.”
Reversing the data mindset
Most enterprises have never had a conversational relationship with their data. Organizations with a deep well of traditional BI expertise have two major cultural hurdles to overcome:
- A deep entrenchment in traditional data warehousing methods. Traditional data warehouses are not built for either the scale or the speed of the Big Data era, but your data management team may need strong leadership to help them be receptive to a new methodology.
- A lack of data curiosity. Because traditional BI was built to answer questions that are contained in a row-oriented, relational database management system (RDBMS), over time the data team learns to limit its data inquisitiveness. Business leaders must adopt and model new ways of thinking—not “What data do we have,” but “What data should we have.”
J. Paul Getty once said, “In times of rapid change, experience could be your worst enemy.” Avoid miring your analytics transition in unproductive ruts by changing the game. Challenge the organization to think differently about data and to ultimately change the status quo.
- Become familiar with the available data sources. Think beyond databases to less familiar and unstructured sources of data, such as social media, email, or video.
- Look into new data practices in your industry. Evaluate new ideas as they emerge, and champion the best ones for adoption.
- Challenge IT. You’ll need to acquire the data, tools, and skills that go beyond your traditional RDBMS.
- Partner data specialists with business stakeholders. Involve the line of business—which has the most actionable insights into your desired analytics results—to achieve the most gain from your new, conversational data initiatives.
To learn more about the possibilities that emerge when a business combines Big Data with advanced analytics power, read the white paper “The Disruptive Power of Big Data,” and read the full Cardlytics case study.
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