Gartner: 5 Of The Biggest Big Data Myths Debunked

Debunking Big Data

Now that big data is a major trend across the IT channel, misconceptions are cropping up and throwing things off, according to new research from Gartner. Those misconceptions, the research firm said, can make it hard for solution providers to know what path to take.

Alexander Linden, Gartner research director, noted in a press release that now's the time for IT leaders to cut through the hype around big data.

"Big data offers big opportunities, but poses even bigger challenges. Its sheer volume doesn't solve the problems inherent in all data," Linden said. "IT leaders need to … base their actions on known facts and business-driven outcomes."

Data Lakes Will Replace The Data Warehouse

Gartner says it's "misleading" for vendors to position data lakes as replacements for data warehouses or as critical elements of customers' analytical infrastructure.

A data lake's foundational technologies lack the maturity and breadth of the features found in established data warehouse technologies, researchers said.

"Data warehouses already have the capabilities to support a broad variety of users throughout an organization. … Leaders don't have to wait for data lakes to catch up," said Nick Heudecker, Gartner research director.

Many organizations get stuck at the pilot stage because they don't tie the technology to business processes or concrete use cases.

Data Warehouses For Advanced Analytics Are Useless

Advanced analytics projects use data warehouse for analysis, according to Gartner's findings. In other cases, information leaders refine new data types that are part of big data to make them suitable for analysis.

"They have to decide which data is relevant, how to aggregate it and the level of data quality necessary," the research firm said in a statement, "and this data refinement can happen in places other than the data warehouse."

Gartner reports its participants found building a data warehouse to be "time consuming" and "pointless," but deeper research proves otherwise.

New Technology Means There's No Need For Data Integration

A large misconception surrounding big data lies in the fact that IT providers don't think there's a need for data integration.

This comes as organizations are struggling to justify the cost of adopting these new technologies, according to Gartner Research Vice President of Information Management Mark Beyer. Gartner researchers found in reality, "most information users rely significantly on ’schema on write' scenarios in which data is described, content is prescribed and there is agreement about the integrity of data and how it relates to the scenarios."

Beyer explained the importance of integration, referring to data lakes with a swimming analogy. If a programmer knows all the language and can go through the data, they know how to swim in the lake and don't need a boat, he said. But he warned about those who jump in the lake with no ability to swim.

Much Data Means No Need To Worry About Data Flaws

Researchers at Gartner said this couldn't be farther from the truth. IT leaders have mistakenly thought with high volumes of data, accuracy isn't always key.

"In reality, although each individual flaw has a much smaller impact on the whole dataset than it did when there was less data, there are more flaws than before because there is more data," said Ted Friedman, vice president at Gartner, in a press release. "Therefore, the overall impact of poor-quality data on the whole dataset remains the same."

He added now that data comes from outside organizations, there is also a greater likelihood of data quality issues.

Everyone's Ahead In Adoption

Gartner found in a study conducted this summer this just isn't the case.

Beyer told CRN that while it can seem like everyone is already in big data due to so much hype, a study with 302 respondents this year found 13 percent actually deployed solutions. Seventy three percent of organizations surveyed, meanwhile, reported they plan on investing or have already invested in the field.

What does this mean for solution providers? Beyer said there is still opportunity in this space in the right vertical. A VAR just needs to choose and go forward from there.

"The biggest challenges that organizations face are to determine how to obtain value from big data, and how to decide where to start," the research firm said in its report.