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Top Analytics and Big Data Trends ahead of Strata Hadoop World San Jose


Top 2015 Analytics and Big Data trends from our readers were Apache Spark, Deep Learning, Real-Time technology, Internet of Things (IoT).



By Gregory Piatetsky, @kdnuggets, Feb 7, 2015.

As a media partner for Strata 2015 Conferences, KDnuggets raffled a free, 2-day conference pass to

O'Reilly Strata + Hadoop Conference, Making Data Work

Feb 17-20, 2015. San Jose, CA, USA

To enter the raffle we asked people to specify 2-3 most interesting trends in Analytics and Big Data in 2015.

One person - Imelda Llanos de Luna - even submitted an essay Two Most Important Trends in Analytics and Big Data in 2015, which we published in KDnuggets.

The winner, chosen by an unbiased random number generator, was Jeffrey Sukharev of ancestry.com.

Others can get a 20% discount code on a regular registration with code: KDNG, unless the conference is sold out.

No single trend was dominant, but most common answers were Apache Spark, Deep Learning, Real-Time technology, and Internet of Things (IoT).

Here is a word cloud and selected interesting answers:

Big Data Analytics Trends Strata 2015
  • Visual interfaces for Hadoop, Spark, and Flink.
  • Health analytics is an important trend in Big Data.
  • BI/analytics will be the top most priority for CIOs
  • real time predictions based on data from internet of things
  • movement toward data sharing standards (ontology) - staring by industry (RealEstate with RESO, etc.) but moving toward the entire landscape
  • increased use by Cities and governments of Open Data initiatives that allow the public to create new data applications
  • evolved toolsets that sit on top of big data infrastructure that make it easier and easier for analysts and SQL jockey's to get at the data stream
  • Creating Analytics and being able to explain how they work to get buy in to move to production
  • Operationalizing Analytics in businesses
  • Customer Experience and Insight
  • Text Analytics in general
  • Hadoop as a service using Docker containers
  • Apache Spark - for real time processing
  • Hadoop security
  • Deep learning becomes available to the masses through myriad offerings
  • AI gains immense traction with the post deep learning algorithms seeing light
  • The data management and analytical platforms start to merge together providing a unified platform for everything
  • Enterprises will continue to make small steps of progress in Big Data adoption but will continue to be frustrated with the trough of disillusion
  • Text analytics , unstructured data tons of it every where , web logs , sensor logs, text
  • poaching of analytics talent from financial institutions doing CRA, lift to digital marketing
  • digital transformation( marketing in social , mobile, a/b testing)
  • Data Agility
  • Organizations Move from Data Lakes to Processing Data Platform
  • Self-Service Big Data Goes Mainstream
  • Increased sensor data collection (e.g. internet of things) and its use in improving human well-being. This will undoubtedly be the platform on which many companies are started and will be a primary area of investment for established companies.
  • The investment of large companies in the data analytics tools space (e.g. Microsoft's acquisition of Revolution Analytics). I believe this will result in more stable implementations of widely used machine learning algorithms and ultimately lead to a broader use of predictive analytics in production environments.
  • Real-time Analytics
  • IoT meets big data
  • Cloud-based data warehousing
  • Hadoop and NoSQL adoption are growing
  • Real-time technology like Apache Spark, Apache Storm, Splunk
  • Analytics in the developing countries
  • Big Data Security
  • Real-time analytics adoption will increase with the proliferation of in-memory technologies and open source streaming ingestion projects.
  • Enterprises appetite for open source will grow driven by successful proof of concepts and increasing cost pressure
  • Spark
  • H2O machine learning platform
  • Deep Learning Algorithms
  • NewSQL, rediscovering the power of traditional RMDBS
  • Python for Data Science
  • Massively scalable Machine Learning

 
Here is a last year's report on top trends ahead of 2014 Strata Santa Clara Conference:

Top Trends in Analytics and Big Data ahead of Strata 2014 Santa Clara.

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