There is business intelligence, big data and now data science.
But how do resellers make money out of this gigantic mass of bits and bytes?
Microsoft says the tools are probably already in your kit bag and it’s on a mission to democratise the data revolution.
Myles Matherson, an application platform and solution specialist with Microsoft NZ, says his company offers an attractive line-up of events around big data for the rest of the year, including something called the Business Intelligence Academy, which will run prior to Tech Ed.
“There are also great online resources, like BI Labs, which are a collection of experimental business intelligence projects and applications made available from internal sources across Microsoft,” says Matherson.
Data science is vital for companies to understand how their customers behave and gain a competitive advantage, Matherson says. The challenge is handling two major mega trends at the same time: managing large amounts of data, and analysing that data.
This is a complex mix. A recent example of data science interacting with business intelligence is the airline KLM offering its customers the ability to choose their long-haul seat partner by the compatibility of their Facebook likes.
“If you think about the kind of brand management that New Zealand organisations have to manage locally and internationally, [it's important to understand] things such as sentiment analysis, whether they have good stories or bad stories, whether they have good tweets or bad tweets and if they have good Facebook traffic or bad Facebook traffic,” says Matherson.
Matherson believes sentiment analysis can drive good outcomes for customers, a capability Microsoft is embedding, for example, in a PowerPivot solution that analyses Twitter feeds to measure sentiment.
“There are about 70 percent of business users today that may not have access to meaningful business intelligence to support their decisions making processes,” Matherson says. “What we’re trying to do is make business intelligence and concepts like data science not only acceptable, but also, in a cost effective way, to leverage the existing investment that customers have in Microsoft technology.”
Out of the cloud
Matherson says data science could be sold as a service, either from a consulting or technical standpoint. “The field of data science is also becoming more service-oriented with resources like the Windows Azure PaaS [Platform as a Service] Marketplace.”
Microsoft also provides tools such as PowerPivot, PowerView, Data Mining and Hadoop on Windows Azure, which are intended to give users access to “meaningful information” through tools they’re already familiar with.
“We have some interesting technologies in there that actually allow data scientists to be able to do pattern matching that they wouldn’t necessarily be able to do with Excel or relational data bases,” Matherson says.
Connecting PowerPivot to Hadoop on Azure, for example, allows users to take unstructured data and tap it in ways a traditionally written query can not. Users could create a “tabular-based model with memory that requires different data sources that aren’t integrated in any traditional form,” he says.
“They need to create that integration as proof or create the proof for a hypothesis that they’re trying to test. That’s what PowerPivot can allow a data scientist to do.”
Matherson says resellers can collaborate with Gold BI Partners to work on customer projects to understand the value of the capabilities of data science to add value to all their data sources.
“Microsoft has six Gold BI Partners in New Zealand today. These organisations help customers understand their data and analytics requirements and do proof of concepts around the technology.”