Cloud Analytics Consortium presents: Analytics in the Cloud: Ready for Primetime

Altaz Bhanji, Dan Ross, Darren Cunningham, Howard Dresner, John Santaferraro, Ralph McMullen, Steve Stone
Join a group of knowledgeable and respected industry thought leaders as they discuss their views about how organizations can best prepare for success with DW/BI solutions in the cloud. Highly reputed independent analyst Howard Dresner who brings 30+ years of IT and BI experience will participate on the panel to provide valuable insights on the future of cloud-based DW/BI solutions. Howard will be joined by senior executives from best-in-class technology organizations including Informatica, MicroStrategy, Netezza, ParAccel and Teradata.

Join us to learn:

* Why more companies are using cloud-based DW/BI solutions now, more than ever before
* About industry solutions for concerns around security, performance, and reliability
* How to evaluate whether a cloud DW/BI solution is right for you
* Cloud adoption or migration strategies for any size business
Dec 6 2012
51 mins
Cloud Analytics Consortium presents: Analytics in the Cloud: Ready for Primetime
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  • My Favourite Pie (chart): Simple Rules for Clear and Attractive Visuals Jul 15 2015 9:00 am UTC 45 mins
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    Do you want to deliver information in an effective and efficient way? Even when the attractiveness of a report is important, beauty is in the eye of the beholder. Join this session where Markus will show you some simple rules for helping end-users to understand the story their data is trying to tell.

    You will see how you can implement those rules with different tools from Microsoft’s BI stack – resulting in clear and concise information delivered through beautiful dashboards. You will also learn how to identify sub-optimal dashboards and what you can do to improve them.
  • Big Reference Data: challenges and opportunities in exploiting large data sets Jun 25 2015 9:00 am UTC 45 mins
    Henrik Liliendahl Sørensen, Data Quality & Master Data Management professional, iDQ
    Reference data are data that is defined and maintained outside the organisation who is using the data. Traditionally these have been small datasets like a country list. Parallel to the rise of big data in general reference data being used for both operational and analytical purposes is also growing in terms of volume, velocity and variety.

    This webinar takes you through the different kinds of big reference data, the challenges and the opportunities in exploiting large sets of reference data from the outside.
  • The Importance of BCDR as Storage Explodes Jun 24 2015 4:00 pm UTC 45 mins
    Seth Robinson, Sr. Director Technology Analysis, CompTIA
    Data is exploding—to the tune of doubling in size every two years. Of course, storage is exploding too as businesses look for ways to hold on to all their data as they analyze and extract insights. With all this growth, business continuity and disaster recovery are areas that can sometimes be overlooked. This webinar will discuss the growth of data and why it is becoming even more important for businesses, then explore the basics behind building a BC/DR strategy that will ensure smooth operations.
  • 2-Tier Business Intelligence: Embrace it or be left behind Jun 24 2015 10:00 am UTC 45 mins
    Richard Neale, EMEA Director, Birst
    Organisations are struggling to reconcile two incompatible tiers of BI: decentralised end users adopting discovery tools and centralised BI/IT teams managing legacy analytics environments. Instead of combining these two worlds, organisations are fighting an internal battle over discovery vs. BI – freedom vs. governance – missing a massive opportunity. Learn how forward-thinking companies are outperforming their competition by harnessing the power of 2-tier BI and Analytics in a world where central BI teams work in collaboration with decentralised business units.
  • 3 Greatest Challenges for Data Management in Education Jun 10 2015 5:00 pm UTC 45 mins
    Guest Speaker: Mark Lamson, Director of IT at Westerly, RI Public School System
    These days, every aspect of educational development creates digital data. Students, faculty, and staff are continually creating files for assignments, lectures and lesson plans, lab and field research, plus the administrative “paper trail”, challenging you, the IT manager, to secure, protect, and manage the growing data sprawl. Schools are just as susceptible to security breaches as other organizations and must comply with stringent data privacy regulations, all while supporting a diverse and constantly changing user base.

    Join guest Mark Lamson, Director of IT at the Westerly, RI public school system, and David Stevens, Technical Marketing Manager at DataGravity, as they explore ways that local school districts, colleges and universities can use automated file and data analysis to reduce complexity and better serve their constituents. You’ll learn strategies to:

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    •Rein in data growth and storage utilization
  • DevOps State of the Union 2015 Jun 9 2015 6:00 pm UTC 45 mins
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    In this webinar, we will give an overview of the state of DevOps in 2015, and cover all relevant methodologies and technologies that DevOps teams and engineers are talking about.
  • Experiments in Deep Learning May 28 2015 6:00 pm UTC 60 mins
    Patrick Hall, Senior Associate Research Statistician Developer, SAS
    The human brain makes it look easy. What our eyes see, we decode immediately and effortlessly. But is it that simple? In truth, how we process images is staggeringly complex. Inspired in part by our remarkable neurons, deep learning is a fast-growing area in machine learning research that shows promising breakthroughs in speech, text and image recognition. It’s based on endowing a neural network with many hidden layers, enabling a computer to learn tasks, organize information and find patterns on its own.

    Recently, SAS took on a classical problem in machine learning research, the MNIST database, a data set containing thousands of handwritten digit images. Learn how we did – and what it reveals about the future of deep learning.
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    The ability of software to recognize patterns in usage, data or other inputs to improve a user’s experience & productivity is an expected attribute of modern software. In this webinar, Will Davis and Tye Rattenbury discuss how Trifacta is building intelligent software that incorporates learning to make the process of wrangling data more intuitive and efficient.
  • Ask, Measure, Learn May 28 2015 4:00 pm UTC 45 mins
    Lutz Finger, Director of Data Science and Data Engineering, LinkedIn; Author, "Ask, Measure, Learn"
    We do not want Big Data! We want the right data to answer the right questions!

    Data is changing our world. Predictions using massive data not only have improved many products. At the same time, they have, in some industries, disrupted business models and created new ones.

    What does an organization need to do to generate a new competitive advantage out of data? The answer might be surprising. “Change the state of mind.”

    Companies often do not need big data. They essentially want small and actionable advice. Some predictions will need big data to surface relevant information, but not all. The key to success for many companies, however, is to enable “data­driven” decision making. Lutz will discuss the steps he has used in starting and developing his own company (later sold to WPP), as well as how he leads LinkedIn’s data science team.

    A) Change the state of mind!
    Enable everyone in the company to ask “data driven” questions. Lutz will show how this is the hardest part of the on­going exercise, but why most businesses actually can achieve this with their current strategic abilities. Using examples we will learn what is the best way to formulate the “Ask”.

    B) What data?
    Data can be a source of disruption & innovation. Business models change because new data sources and enhanced computational power allows new services or improve old services. But which data to use? Domain knowledge is often more important than having “Big Data". Lutz will introduce a framework on how to think about data.

    C) How to build a Data Team?
    How can organizations build up data capabilities within your team. Contrary to the common discussion that a data scientist are not ‘hard to find’. Lutz will explain how every company can create a data science organization by just mixing the right skillets.
  • Statistical Computing-R & Visual Analytics: Data Science at the Speed of Thought May 28 2015 4:00 pm UTC 45 mins
    Bora Beran, PhD, Program Manager, Tableau
    Do you spend days on data science projects, only to struggle building them into presentations that management can understand? Do you spend more time exploring and understanding your data, before even beginning to write one line of a model? Do you have a hard time working through other departments to get to your data in the first place?

    Tableau is a visual reporting application that connects directly to R. It’s designed for you, the domain expert who understands the data. Its drag-and-drop interface allows you effortlessly connect to libraries and packages, import saved models, or write new ones directly into calculations, visualizing them in seconds.

    This webinar will show you how to:
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    Join us to see how you can use drag and drop data visualization alongside R to speed up your data science projects and get them in front of more eyes, leading to smarter, data-driven business decisions.
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    Dean Malmgren, Partner and Data Scientist, Datascope Analytics
    When you hear someone say, “that is a nice infographic” or “check out this sweet dashboard,” many people infer that they are “well-designed.” Creating accessible (or for the cynical, “pretty”) content is only part of what makes good design powerful. The human-centered design process is geared toward solving specific problems. This process has been formalized in many ways (e.g., IDEO’s Human Centered Design, Marc Hassenzahl’s User Experience Design, or Braden Kowitz’s Story-Centered Design), but the basic idea is that you have to explore the breadth of the possible before you can isolate truly innovative ideas.

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    Dr. Nilesh Karnik, Chief Data Scientist, Aureus Analytics
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    Parviz Peiravi, Principal Architect for Big Data, Intel; Anant Chintamaneni, VP of Products, BlueData
    Big Data analysis is having an impact on every industry today. Industry leaders are capitalizing on these new business insights to drive competitive advantage. Apache Hadoop is the most common Big Data framework, but the technology is evolving rapidly – and one of the latest innovations is Apache Spark. 
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    - How to leverage the power of Spark for iterative algorithms such as machine learning
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    SAS Marketing
    Get your data right where you want it by loading it into – or out of – Hadoop so it’s ready and available for reports, visualizations or advanced analytics. Sound easy? It is. Because you can do it all yourself.

    SAS Data Loader for Hadoop empowers you to manage your own data without writing code.
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    Luis Pedro Coelho, Postdoctoral Researcher at European Molecular Biology Laboratory
    Machine Learning has already started to show its potential and will continue to grow in importance, while at the same time, it is often oversold as its pitfalls and costs are not sufficiently emphasised.

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    -How good UX design can amplify or mitigate the failures of the ML
    component of the system
    -How expectation management is important (why do we accept the need to train people, but not computers?)
    -Why domain knowledge is almost always necessary, but it's rarely
    -Why there will still be a need for data scientists in 20 years (rather
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  • Augmenting MySQL with Big Data & NoSQL Options Recorded: May 13 2015 60 mins
    David Murphy, Lead DBA , ObjectRocket by Rackspace
    How do you know which technology is right in todays database world, we will explore the range of technologies from MySQL/Percona/Maria to Xtra Cluster to Mongo to Redis and how you can fit all of these together to form a path way for your data. Not one technology fits everything but together you can use the right tool for the right job, and make the data flow seamlessly between them to range from short session data to longer term reporting data and everything between. We are at the new frontier in database lets work on a new toolset to prepare you for it.

    David is currently the Lead DBA for Object Rocket by Rackspace, where he works on sharding, mongo, tool building, very large-scale issues, and high performance mongo architecture. Before that he was the MySQL/NoSQL Architect for Electronic Arts, after working in segments from data centers to high performance advertising with skills ranging from programing to hardware/network design he brings a top down view into troubleshooting and tuning. He enjoys large-scale operational tool building, high performance OS and Database tuning, and extending mongo to improve operations team both large and small.
  • Generating Value From Your Data Recorded: May 11 2015 51 mins
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    “Data is a corporate asset” has achieved platitude status, yet companies are still looking for the answer to the age-old question of “How much is our data worth?” Executives have become increasingly aware of the value of data (internally and externally) and are attracted to potential new revenue streams from information-based products and services.

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    Tamara Dull, Director of Emerging Technologies, SAS Best Practices
    Optimized. Efficient. Agile. Reliable. Stable. Structured. Everything that is important to a technology geek and everything the world of big data seems to elude. Travelling through the world of big data can seem like a daunting journey through unchartered territory.

    This session will provide you - the weary, travelling technical intellectual - with a guide to the unstructured, unfamiliar, and ever-changing world of big data, Hadoop, and open source software. We will look at the components and tools in the open source Hadoop ecosystem that are needed for managing storing, managing and acting on data of all shapes, sizes and types. We will also explore the plusses and minuses of integrating open source software in your traditional, proprietary environment.
Make smarter moves with your big data management
Make smarter moves with your big data management

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  • Title: Cloud Analytics Consortium presents: Analytics in the Cloud: Ready for Primetime
  • Live at: Dec 6 2012 5:00 pm
  • Presented by: Altaz Bhanji, Dan Ross, Darren Cunningham, Howard Dresner, John Santaferraro, Ralph McMullen, Steve Stone
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