In 2017, systems that support large volumes of data will
continue to rise. The market will demand platforms that help data custodians
govern and secure big data, while empowering end users to analyse that data
more easily than ever before. These systems will mature to operate well inside
of enterprise IT systems and standards. Furthermore, the focus on big data
analytics skills will continue to grow as it becomes a more central focus for
enterprises across industries.
In Singapore, specifically, the Economic Development
Board (EDB) has predicted that the data analytics sector will likely add
$1 billion in value to the economy by 2017. The discussion drives our list of
the top big data trends for the following year.
These are the predictions for 2017:
A smarter everything, with big data skills:
In
Singapore itself, we have already seen the government launch several incentives
to encourage the workforce to develop these skills, while more academic
institutions offer relevant courses to their students. This will continue to
take main stage in 2017.
Variety drives big-data investments:
Gartner
defines big data as the three Vs: high-volume, high-velocity, and high-variety
information assets. While all three Vs are growing, variety is becoming the
single biggest driver of big-data investments, as seen in the results of a
recent survey by New Vantage Partners. This trend will continue to grow as
firms seek to integrate more sources and focus on the “long tail” of big data.
Data
formats are multiplying and connectors are becoming crucial. In 2017, analytics
platforms will be evaluated based on their ability to provide live direct
connectivity to these disparate sources.
The convergence of IoT, cloud, and big data
create new opportunities:
It
seems that everything in 2017 will have a sensor that sends information back to
the mothership. In smart cities and nations, like Singapore, analysts have
commented that products from the IoT sector will continue to feature. A year
ago, Frost and Sullivan also projected that the number of connected devices
will increase to 50 billion units globally in five years; this is equivalent to
each person having ten connected devices.
Across
the region, IoT is generating massive volumes of structured and unstructured
data, and an increasing share of this data is being deployed on cloud services.
The data is often heterogeneous and lives across multiple relational and
non-relational systems, from Hadoop clusters to NoSQL databases. While
innovations in storage and managed services have sped up the capture process,
accessing and understanding the data itself still pose a significant last-mile
challenge.
As
a result, demand is growing for analytical tools that seamlessly connect to and
combine a wide variety of cloud-hosted data sources. Such tools enable
businesses to explore and visualize any type of data stored anywhere, helping them
discover hidden opportunity in their IoT investment.
Big data grows up: Hadoop adds to enterprise
standards:
We’re
seeing a growing trend of Hadoop becoming a core part of the enterprise IT
landscape. And in 2017, we’ll see more investments in the security and
governance components surrounding enterprise systems. Apache Sentry provides a
system for enforcing fine-grained, role-based authorization to data and
metadata stored on a Hadoop cluster. Apache Atlas, created as part of the
data governance initiative, empowers organisations to apply consistent data
classification across the data ecosystem. Apache Ranger provides centralized
security administration for Hadoop.
These
capabilities are moving to the forefront of emerging big-data technologies,
thereby eliminating yet another barrier to enterprise adoption.
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