Big data has finally hit its stride in enterprise and it keeps growing. Here are the trends that will define big data in 2016.
If technology had a Zodiac, 2015 would be the year of big
data.
More businesses used data of all forms to make decisions,
and more consumers learned more about their life and their habits with the help
of data.
With this momentum, the year ahead will be a big one for the
information economy. Here are five trends in data usage that we expect to see
in 2016.
1. Data as a corporate asset
It's one thing to acknowledge the value of data in theory,
and it's another to act on that value. Gartner's Doug Laney said that
organizations have been giving it lip service, but not behaving as though they
see data as an asset in terms of the way they're collecting, generating,
managing, and deploying it. However, that is changing in that more
organizations are thinking about data as a corporate asset.
The problem is that information is "not a recognized
balance sheet asset," Laney said. And, that inhibits truly engaging data
in the business.
"As with any asset, all forms will be collected,
maintained, and utilized," said Rob Thomas, vice president of product development
for the analytics platform at IBM. "Not just the traditional structured
data, but unstructured, text, Internet of Things (connected devices),
etc."
2. Deeper customer data
One of the most valuable types of data available to
businesses is customer data. Whether it is consumer retail customers or
enterprise clients, knowing how they approach the product is crucial. However,
customers are approaching businesses from different angles and different
platforms, and companies are finding it difficult to keep up.
"In 2016, we'll see more focus on a combination of
deterministic (log-in / authentication) and probabilistic (data management
platforms) methods to bridge this gap," said Brent Dykes, evangelist for
customer analytics at Adobe. "With growing privacy concerns from
consumers, brands will need to be careful about how they use this cross-device
customer data in their marketing efforts."
3. Growing data variety
Customers are still one of the driving data forces for many
brands. But, the types of data collected on customers is expanding well beyond
where they clicked on a webpage or what their perceived demographic is.
"As mobile becomes the primary digital channel for many
brand interactions, it offers a rich, new type of data—location data at macro (GPS)
and micro (LE Bluetooth beacons) levels," Dykes said. "Location data
is a valuable arrow in marketer's quivers that can be used for
location-specific, in-context offers and personalization."
In addition to capturing customer information, businesses are
moving into a host of other areas to capture the data associated with it.
"There's been an awakening, if not yet a complete shift
in focus, on the value of data that streams from things—whether it's cars, or
refrigerators, or drones, or whatever that is," Laney said. "That's
the next wave of big data."
Additionally, certain industries are looking at other unique
data points and how they affect the business. For example, Laney said, some
lenders look at social media to determine potential risk in an investment. Also
industries like manufacturing, distribution, and retail look at weather data
and its effect on their organization.
Moving beyond next year, we'll likely see even more data
types being accounted for. Laney said, within the next decade, he wouldn't rule
out the use of biometric data or even DNA. And, as the variety of data
increases, vendors need to do more to accommodate it.
4. Data by industry
As with many tech trends, certain industries get a head
start as early adopters in the space. Big data is no exception. Financial
services, technology companies, retail, and telco are all leaders in leveraging
data in their workflows.
"Because they are further down the maturity curve, they
will be generating significant benefits from their early-adopter investments in
technology, people, processes, and culture," Dykes said.
In 2016, these leaders will likely continue to widen the gap
between themselves and the laggards in other markets. Although, there are
industries and verticals that are taking an alternative approach, or looking at
different types of data, and gaining value from it.
"We're also seeing major breakthroughs in industries
such as automotive, aerospace, electronics, industrial products, oil and gas,
and energy and utilities where the larger focus is on analyzing equipment and
machine-generated data to predict potential maintenance issues and optimize
manufacturing productivity," Thomas said.
5. Dealing with privacy
With privacy concerns at an all time high, the data collection
practices of many organizations are continually coming into question. In many
instances, the issue that is raised has to do with who owns the data that's
collected.
"I think it's the idea that people think there's such a
thing as data ownership, and, because data is so fungible and replicable, that
idea of data ownership really is nonsense," Laney said. "It's all
about data rights and privileges."
As such, Laney said, organizations that are producing or
capturing data needs to focus on defining rights and privileges associated with
that data.
Additionally, because most people don't want to be governed
or policed, they'll need to position data governance in a way that showcases
improved value in the data.
Original Source: Conner Forest, Techrepublic
