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HP Software's community for IT leaders // November 2012

What your data could be telling you

HP Software’s CIO explains how turning Vertica’s analytics tools on itself let HP unleash greater innovation and identified significant savings—all by being able to ask the right questions.
For many data scientists, innovation is just out of reach. They might have massive data stores, rich with potential business insights, but their reporting system can’t unlock them.
“Traditional reporting systems are good at giving information about what happened in my business yesterday, but they’re not good at nearly real-time or predictive analytics,” says Saum Mathur, CIO of HP Software. “They can’t really tell me what customers are thinking today or how I can improve my business tomorrow. To innovate and keep an organization moving in the right direction, that’s just not enough.”
This waste of a big data opportunity is a crossroads for information management executives, who must rally their organizations around the pressing need for business intelligence agility. Those who use next-generation analytics tools to transform the business and improve the bottom line will succeed.

The problem with data warehouses

Traditional data warehouses are designed to tell organizations what happened in the past, and they’re extremely sensitive to data structure and quality. 
“In a financial reporting role this makes sense,” Mathur says. “For example, we have to report financials to the Street, and accuracy is absolutely critical. In other cases, though, we’re more interested in patterns and trends, with a relatively small window to act on data before its value diminishes. Innovation requires speed, agility, and the ability to react to those emerging trends. This can conflict with traditional IT demands for data quality and conformance to strict enterprise data standards.”
Instead, you need to be able to load and analyze huge volumes of data from multiple sources very quickly. Once you can do this, you open the door to ad-hoc analysis, with the line of business and information management teams collaborating to interact with the data. When you can ask questions, get immediate results, and then iterate the questions accordingly, true innovation can happen.

Innovation begins at home

Having the same innovation goals as other organizations, HP applied its own advanced analytics technology, the HP Vertica analytics platform, to a number of its biggest data challenges. Highlights from HP’s biggest Vertica wins to date include:

Preventing service issues and improving quality

HP’s latest servers are built with the ability to “phone home” to report large volumes of detailed machine data about their status. By analyzing all of this performance data, HP discovered a particular pattern of hardware and software changes that could result in a warranty event for its customers.
“There are three key benefits of this insight,” Mathur says. “First, you can engage with a customer to prevent a problem in their environment, and that leads to a more satisfied customer. Next, it prevents a future cost to the company that would have come with a warranty call. Lastly, you can use the insight you gain from the analysis and feed it back into development teams to improve and enhance the product.”
During a recent analysis, HP determined that an improvement of just 1 percent in quality could save $4.5 million in costs to the company.

Improving forecasting

Vertica also helped HP more accurately forecast payments to channel partners. “Forecasting is both an art and a science,” Mathur says. “To improve forecasting ability, you have to analyze data, detect patterns, and make it more of a science and predictable.”
With one person’s effort over the course of one week, HP was able to improve its quarterly forecasting ability by $10 million.

Reinvention, not replacement

Traditional data warehouses are not obsolete—far from it. Instead, organizations need to use cutting-edge analytics tools to understand their data and identify valuable data patterns, then begin tracking and reporting on those patterns in their enterprise data warehouse.
“A typical data warehouse project can take months, because you have to understand and model the data first—ask the business what their reporting needs are,” Mathur says. “Until those questions are answered and built, there is no value to the business. With tools like Vertica, you can work with the business to discover data, reporting, and analytics needs jointly. In a very agile way, you can deliver business value during the discovery process.”
Granted, it’s more ad hoc in nature, but Mathur notes that once discovery and analytics requirements are settled, you can move the data and intelligence to EDW for more repeatable analytics and intelligence going forward.
“Furthermore, the ability to expunge, load, reload and mine data several times a day really increases the speed of innovation,” he adds. “That’s something you just can’t do with a traditional data warehouse.”
For many organizations, the biggest challenge will be changing the data management culture. Senior business intelligence experts may be reluctant to accept new processes that move away from traditional data warehouses. They may be unfamiliar with the capabilities of next-generation data analytics systems, or uncomfortable with tools and development methodologies that require retraining. To be successful, the initiative needs a strong, confident executive who will champion the innovation opportunities that lie ahead. Fortunately, the benefits of next-generation analytics speak strongly for themselves.

Read more about real-time loading and querying at


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