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Top 8 Big Data Trends for 2016

Every year at Tableau, we look back at the last 12 months and evaluate the ways in which technology is changing the face of business decisions. That discussion drives our list of top big data trends for the following year.

In this 45-minute webinar, explore:

Emerging trends in big data
Tableau experts' take on the changing big data landscape
Considerations for your 2016 big data strategy
Tune in to submit questions during the live Q&A with our panelists and attendees.
Recorded Mar 10 2016 45 mins
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Presented by
Dan Kogan, Eric Hannell, and Jeff Feng
Presentation preview: Top 8 Big Data Trends for 2016

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  • The End of Enterprise Software Dec 8 2016 7:00 pm UTC 45 mins
    Merav Yuravlivker, Co-founder and CEO, Data Society
    Is it worth it for companies to spend millions of dollars a year on software that can't keep up with constantly evolving open source software? What are the advantages and disadvantages to keeping enterprise licenses and how secure is open source software really?

    Join Data Society CEO, Merav Yuravlivker, as she goes over the software trends in the data science space and where big companies are headed in 2017 and beyond.

    About the speaker: Merav Yuravlivker is the Co-founder and Chief Executive Officer of Data Society. She has over 10 years of experience in instructional design, training, and teaching. Merav has helped bring new insights to businesses and move their organizations forward through implementing data analytics strategies and training. Merav manages all product development and instructional design for Data Society and heads all consulting projects related to the education sector. She is passionate about increasing data science knowledge from the executive level to the analyst level.
  • Predictive APIs: What about Banking? Dec 8 2016 12:00 pm UTC 45 mins
    Natalino Busa, Head of Applied Data Science at Teradata
    The best services have one thing in common: a superb customer experience. Banking services are no exception to this rule, and indeed the quest for an effortless, well informed, and personalized customer experience is one of the main goals of today's innovation in digital banking services.

    According to what Maslow has described in his "pyramid of needs", customers are seeking a more intimate and meaningful experience where banking services can actively assist the customer in performing and managing their financial life. Predictive APIs have a fundamental role in all this, as they enable a new set of customer journeys such as automatic categorization of transactions, detecting and alerting recurrent payments, pre-approving credit requests or provide better tools to fight fraud without limiting legitimate customer transactions.

    In this talk, I will focus on how to provide better banking services by using predictive APIs. I will describe the path on how to get there and the challenges of implementing predictive APIs in a strictly audited and regulated domain such as banking. Finally, I will briefly introduce a number of data science techniques to implement those customer journeys and describe how big/fast data engineering can be used to realize predictive data pipelines.

    The presentation will unfold in three parts:

    1) Define banking services: Maslow's law, modern vs traditional banking
    2) Examples predictive and personalized banking experiences
    3) Examples of data science and data engineering pipelines for banking and financial services
  • Cloud Customer Architecture for Big Data and Analytics Dec 7 2016 7:00 pm UTC 60 mins
    Heather Kreger, Gopal Indurkhya, Manav Gupta, Christine Ouyang from the Cloud Standards Customer Council
    Using analytics reveals patterns, trends and associations in data that help an organization understand the behavior of the people and systems that drive its operation. Big data technology increases the amount and variety of data that can be processed by analytics, providing a foundation for visualizations and insights that can significantly improve business operations.

    In this webinar, the Cloud Standards Customer Council will discuss how to support big data and analytics capabilities using cloud computing. The speakers will walk through a cloud reference architecture and cover the various considerations and best practices for building big data and analytics solutions in the cloud.
  • From the intelligence driven datacenter to an intelligence driven business Dec 7 2016 2:00 pm UTC 45 mins
    Matt Davies, Head of Marketing EMEA, Splunk, & Sebastian Darrington, EMEA Director, Big Data & Analytics Solutions, Dell EMC
    Leveraging Big Data and Analytics to create actionable insights.

    Splunk & Dell EMC will share insights into the challenges & opportunities customers are seeing in the market – with the ‘needs to’; reduce costs and improve efficiency within IT (operational analytics), improve Compliance (security analytics) & implement Shadow IT due to the business not receiving the right service from IT. CIO Priority is keeping the lights on and so on…

    Dell EMC & Splunk combined strengths are helping numerous organizations to ‘leverage Big Data and Analytics to create actionable insights’.
  • Analytics in the Cloud Dec 7 2016 1:00 pm UTC 45 mins
    Natalino Busa, Head of Applied Data Science at Teradata
    Today, data is everywhere. As more data streams into cloud-based systems, the combination of data and computing resources gives us today the unprecedented opportunity to perform very sophisticated data analysis and to explore advanced machine learning methods such as deep learning.

    Clouds pack very large amount of computing and storage resources, which can be dynamically allocated to create powerful analytical environments. By accessing those analytics clusters of machines, data analysts and data scientists can quickly evaluate more hypotheses and scenarios in parallel and cost-effectively.

    The number of analytical tools which is supported on various clouds is increasing by the day. The list of analytical tools spans from traditional rdms databases as provided by vendors to analytics open sources projects such as Hadoop Hive, Spark, H2O. Next to provisioning tools and solutions on the cloud, managed services for Data Science, Big Data and Analytics are becoming a popular offering of many clouds.

    Analytics in the cloud provides whole new ways for data analysts, data scientists and business developer to interact with each other, share data and experiments and develop relevant insight towards improved business processes and results. In this talk, I will describe a number of data analytics solutions for the cloud and how they can be added to your current cloud and on-premise landscape.
  • Getting to Caprica - Making VR Really Usable Nov 29 2016 5:00 pm UTC 45 mins
    David Burden - CEO, Daden Limited, an immersive learning and visualisation company
    This webinar will look at the challenges currently facing VR across a variety of "serious business" use cases from education and training to data visualisation and what the technology needs to do in order to get beyond the "wow" and move into being a productive, useful and truly in-demand technology.
  • Video interview: What is data wrangling? Nov 23 2016 12:00 pm UTC 15 mins
    Joe Hellerstein, Chief Strategy Officer at Trifacta
    Listen to our interview at Big Data LDN with Joe Hellerstein, Chief Strategy Officer at Trifacta.

    Joe will answer:

    - As the founder of Trifacta, tell us a bit about your company and just what is data wrangling?
    - How does it differ from ETL?
    - You have just announced a new server edition of Trifacta, can you tell us more this?
    - Can you give us some examples of how your customers are leveraging Big Data?
    - What makes a big data project successful?
    - What advice would you give to companies starting out with a big data project?
    - What are the biggest hurdles to overcome?
    - What use cases are the most prevalent at the moment and will that change over time?
  • Video interview: Data challenges when developing your own cloud applications Nov 22 2016 12:00 pm UTC 15 mins
    Patrick McFadin, Chief Evangelist for Apache Cassandra at DataStax
    Listen to our interview at Patrick McFadin, Chief Evangelist for Apache Cassandra at DataStax.

    Patrick will discuss:

    1) What are some of the challenges data professionals face when developing their own cloud applications?
    2) How important is it to provide end-users with dealing with real-time insights?
    3) Why is your database choice critical for transforming customer experience?
    4) How have customer expectations changed in the past 5 years?
  • Video interview: How can search engines be used to make sense of Big Data? Nov 21 2016 12:00 pm UTC 15 mins
    Charlie Hull, Owner & CEO at Flax
    Listen to our interview at Big Data LDN with Charlie Hull, Owner & CEO at Flax.

    Charlie will discuss:
    -Do search engines and Big Data systems share any history?
    -How can search engines be used to make sense of Big Data?
    -What are the options available for those wanting to add full-text search to their Big Data stack?
    -Why is open source search a better choice than a closed, commercial alternative?
  • Video interview: Real-world cases to bring Big Data out of dev & into production Nov 18 2016 12:00 pm UTC 15 mins
    Ted Orme, VP Technology EMEA at Attunity
    Listen to our interview at Big Data LDN with Ted Orme – VP Technology EMEA for Attunity.

    Ted will talk about the evolution of Hadoop from a simple batch automation engine to the analytical hub of the enterprise. He will focus on real world examples and best practice architecture to bring Big Data out of dev and test, and into production.

    Ted will also share insight into the future of real-time streaming and how CDC technologies are essential to any Kafka implementation.
  • Video interview: Solving challenges of the data tsunami created by the IoT Nov 17 2016 12:00 pm UTC 15 mins
    Dave McCrory, CTO, Basho
    Listen to our interview at Big Data LDN with Dave McCrory, CTO at Basho.

    Dave will discuss:
    -Riak, the world's most resilient NoSQL database and what makes Riak unique in the category
    -How Riak handles and resolves scalability and availability challenges when dealing with Big Data in this new connected world
    -How his team at Basho is helping to solve challenges of too much data being created by the IoT
    -The definition of "Data Gravity"
    -How and why Agglomeration is a game changer for businesses
    -How to get started on Riak and is it available open-source?
  • Video interview: Deep learning and its intersection with the Hadoop ecosystem Nov 16 2016 12:00 pm UTC 15 mins
    Sean Owen, Director of Data Science at Cloudera
    Listen to our interview at Big Data LDN with Sean Owen, Director of Data Science at Cloudera.

    Sean will talk about the deep learning framework its seamless deployment in Hadoop clusters. He will also discuss some detailed applications and use cases to further visualize this intersection.
  • Video interview: How to make the most out of your data Nov 15 2016 12:00 pm UTC 15 mins
    Sean Jackson, CMO, EXASOL
    Listen to our interview at Big Data LDN with Sean Jackson, CMO at EXASOL AG.

    Sean will give an overview of how you can get the most out of your data -- from cloud-based analytics to data visualization, Sean will break down the challenges you face in your quest to become a data-driven professional.
  • Video interview: The modern data lake - Operationalising Big Data for everyone Nov 14 2016 3:00 pm UTC 15 mins
    Richard Neale, EMEA Director, Birst
    Listen to our interview at Big Data LDN with Richard Neale, EMEA Director at Birst.

    Companies have embraced the concept of the data lake or data hub to serve their data storage and data-driven application needs. However, gaps remain in the maturity and capability of the Hadoop stack, leaving organisations struggling with how to reap the benefits of these data lakes and how to create analytic applications that deliver value to end users.

    For data lakes to succeed, organisations need to learn and understand the differences between these big data scenarios:
    1. Data discovery and exploratory analysis
    2. Analytic applications and operationalisation of analytics across the enterprise

    Richard will examine these two scenarios, where and when each one is appropriate, and how to mature from one to the other..
  • Video interview: Solving common mistakes when dealing with advanced analytics Nov 11 2016 3:00 pm UTC 15 mins
    Shawn Rogers, Chief Research Officer, Statistica
    Listen to our interview at Big Data LDN with Shawn Rogers, Chief Research Officer at Dell Statistica.

    Shawn will tackle the often challenging topic of IoT data and give his advice for making the most out of it, as well as the common mistakes people make when dealing with advanced analytics.

    Shawn will also tell us a bit about The Algorithmic Economy and what it means for the data landscape in the next 5 years.
  • Building Enterprise Scale Solutions for Healthcare with Modern Data Architecture Nov 10 2016 7:00 pm UTC 45 mins
    Ramu Kalvakuntla, Sr. Principal, Big Data Practice, Clarity Solution Group
    We all are aware of the challenges enterprises are having with growing data and silo’d data stores. Businesses are not able to make reliable decisions with un-trusted data and on top of that, they don’t have access to all data within and outside their enterprise to stay ahead of the competition and make key decisions for their business.

    This session will take a deep dive into current Healthcare challenges businesses are having today, as well as, how to build a Modern Data Architecture using emerging technologies such as Hadoop, Spark, NoSQL datastores, MPP Data stores and scalable and cost effective cloud solutions such as AWS, Azure and BigStep.
  • Video interview: Use cases for predictive maintenance & the Big Data impact Nov 10 2016 3:00 pm UTC 15 mins
    Wael Elrifai, Director of Enterprise Solutions (Pentaho)
    Listen to our interview at Big Data LDN with Wael Elrifai, Director of Enterprise Solutions at Pentaho.

    Wael will talk through some use cases for predictive maintenance and how Big Data has impacted these models.

    He will also share some tips for people still struggling with Hadoop and will also go over the different ways to embark on an IoT strategy for your organisation.
  • Embrace a Modern Data Architecture and gain competitive advantage! Nov 10 2016 2:00 pm UTC 45 mins
    Adrian Whitehead, Specialist SE, Dell EMC
    The technology landscape is moving at a fast pace and organisations are struggling to keep up and need to think of new ways of processing, analysing and getting value from the vast array of data sources now available.

    Tune in to listen to a conversation between two technology experts who discuss the current challenges experienced in the big data industry and what tools and infrastructure are being deployed including Spark, Hadoop, Splunk etc. to get value from the massive amounts of data flowing around the globe!
  • How Spireon Turned IoT Data into a Competitive Advantage Nov 2 2016 10:30 am UTC 45 mins
    Ben Tran, Product Manager, Spireon
    Spireon, an IoT company, needed a BI platform that could turn over 3 billion records of data, with a projected growth rate of 3x per year, into operational insights both for their internal teams as well as their customers.

    Watch this webinar and learn:
    - How Spireon used Birst to transform semi-structured data into analytic format
    - Best practices in approaching analytics for data volumes with exponential growth
    - How analytics is used internally by product and customer success teams
    - How Spireon has disrupted the IoT market by creating a data product
  • Dashboard Best Practices Recorded: Oct 25 2016 45 mins
    Carl Edwards, Senior BI Consultant, Yellowfin
    Dashboards are the most important, fundamental, tool for delivering Business Intelligence insights to your users. But, data visualization expert Stephen Few, has declared that most BI dashboards fail. Attend this webinar and learn how to construct best practice dashboards, achieve high ROI and create BI success; not failure.
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  • Live at: Mar 10 2016 5:00 pm
  • Presented by: Dan Kogan, Eric Hannell, and Jeff Feng
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