Story image

Gartner: Big Data is pregnant with analytics

25 Jun 15

We are at the interesting point: big data time is over. It is now big data analytics time.

Many organiszations are at the point when they have figured out how to get data in Hadoop (or other big data stores), but not — how to get the data out and derive value from it. These companies are becoming increasingly nervous under the pressure of rapidly growing amounts of unprocessed data (a.k.a. WRITE ONLY data that nobody will ever read).

The convergence of cloud, mobility and social computing that started several years ago culminated now in the first truly widespread big data analytics use case — the Internet of Things, IoT. Companies in very different industries — insurance, oil and gas, healthcare, transportation and agriculture among many others — are deploying sensors and collecting data, generated by them.

The rise of data lakes reflects the nature of the current point in time. Data lakes signify uncertainty, when organizations want to store more and more data generated with enormous speed, hoping to make sense of this data someday. Companies need a conventional name for a data storage that allows them to keep their options open for future analysis — this is a data lake. The more data is in the lake, the harder it is to separate the signal from the noise. The signal is there, among a myriad of other signals, go fish.

Analytics is the way out of the data lakes, it will help to find value in big data stores. However, analytics is now different: it is not just a clever tool for analysis, but also the whole architecture to put data in the analytic-ready form. And remember, it is big data analytics — different solutions and algorithms are required at scale.

Moore’s law is still hard at work: for example, server memory is measured now in terabytes compared to gigabytes two years ago, so clusters of severs can keep tens of terabytes in memory — this paves the road to fast in-memory analytics. Apache Spark — a fast, in-memory processing and analytical framework — came to focus at the right time, in the right place: it is leading the shift from big data storage to big data analysis.

In early 2014, I wrote in a blog post, “The rocket ship of big data analytics is launched and on its way to orbit.” Happy to report: the rocket ship of big data analytics reached orbit!

By Svetlana Sicular, Gartner

Vertiv reveals new ‘plug-and-play’ data centre options
The new product families are said to enable the rapid deployment of right-sized, just-in-time data centre and power capacity.
Fujitsu takes conservation prize for immersion cooling system
The prize was awarded for the Fujitsu Server PRIMERGY Immersion Cooling System that can reduce power consumption by up to 40%.
5G will propel RAN market to $160b in near future
5G growth is expected to advance at a faster pace than LTE, particularly within the APAC region.
Telstra partnerships boost subsea cable infrastructure
Telstra’s customers across Asia Pacific will soon be able to take advantage of major major boosts to Telstra’s network services and subsea cables.
Expert comment: Google fined US$57mil for GDPR breaches
The committee examining the breaches found two types of breaches of the GDPR.
NTT Com launches Azure stack in Singapore
NTT Communications Corporation (NTT Com) has introduced the Managed Microsoft Azure Stack Solution to its Singapore operations.
Liquid cooling key to silencing a noisy data centre
Data centre are famous for being very noisy, but Schneider Electric's Steven Carlini says liquid cooling infrastructure could change that.
Achieving cyber resilience in the telco industry - Accenture
Whether hackers are motivated by greed, or a curiosity to assess a telco’s weaknesses; the interconnected nature of the industry places it in a position of increased threat