Join leading MVPs for a two track one day event that tackles the delivery of
Enterprise data platforms and analytics solutions.
Please register to attend either track 1 or track 2:
• Track 1 will focus on building the modern enterprise data platform. In a
series of three presentations we will tackle the issues of architecture,
application frameworks, data integration and data exchange; learning all about
the challenges faced by the modern data tier developer. Most importantly, we
will learn how to creatively overcome them by enhancing our processing
efficiency and analytical capability.
Register to attend Track 1
• Track 2 will focus on the creation of Business Intelligence and advanced
analytics solutions that utilise both structured and un-structured data. We will
demonstrate the use of data mining and predictive analytics technologies and
also demonstrate how advanced visualisation technologies can be used by business
users to deliver the insight and action required to drive real value from data.
Register to attend Track 2
10:00am Keynote – Anthony Saxby
Vision and roadmap for the Microsoft Cloud OS Data and Insights
Platform together with two customer success stories of delivering Data Insight
solutions combining key aspects of the platform.
Track 1 - Session Abstracts
11:15am – 12:30am Session 1 – Richard Conway MVP
Building a scalable, high performance Cloud OS Data tier in Azure
One of the most difficult tiers to scale in any application is the data
tier. Data frameworks are numerous these days and often it’s difficult to
determine what you should be using. Windows Azure is a fully featured cloud
platform which support all workloads through many kinds of clustered
In this talk we’ll begin looking at the storage subsystem and how this can be
optimised for SQL Server to offer comparable to on premise performance for a
smaller price point. We’ll showcase Windows Azure storage and show how this can
scale and be used in tandem with relational data to show the right way to build
applications covering aspects of Table and Blob Storage. We’ll look at how
frameworks such as HPC Pack are deployed to Windows Azure virtual machines for
high performance computing over smaller datasets introducing the idea of “Big
Compute”. We’ll also look at other data solutions like Ambari, Spark-Shark and
Storm and see how they scale and cluster together into the new Hadoopv2
1:15pm – 2:30pm Session 2 – Andy Cross MVP
Getting results from HDInsights and noSQL Data platforms
In this talk, Andy will provide tips for getting HDInsights up and
running, building MapReduce jobs and integrating other noSQL database
environments including Document stores, network stores and others into the
Microsoft Cloud OS Data platform
2:45pm – 4pm – Session 3 – James Rowland-Jones MVP
Integrating the worlds of Relational and non-Relational data using Polybase
The world of analytics looks to solve new and interesting data problems
– giving rise to lots of interesting, diverse technology and data sources. This
new, often ‘big’ data can also be born in a variety of shapes and sizes
providing a very challenging environment for the data professional to derive
meaningful insight. One tool isn’t always enough. Consequently data platforms
need to provide a flexible, scalable and integrated solution that unites data
across relational and non-relational paradigms.
In this session you will learn all about data integration with SQL Server
Parallel Data Warehouse (PDW) – Microsoft’s scale out analytics appliance. We
will focus our attention on PDW’s landmark “Polybase” feature as it provides the
glue between relational data structures held in PDW and the non-relational world
Track 2 – Session Abstracts
11:15am – 12:30pm – Session 1 - Horton Works
Analysis and Visualisation Patterns for common Big Data types
Sources of Big Data are turning the conversation from “data analytics”
to “big data analytics” because they hold significant business value. Where to
start can often be quite daunting. As our list of customers grow, we’ve spent
time identifying the “types” of data that land in Hadoop and what we found was
interesting. While every organization is different their big data is often very
similar. For the most part, Hadoop is enabling the collection of massive amounts
of data across six basic types of data: social media activity, clickstream data,
server logs, unstructured (videos, docs, etc) and machine/sensor data from
equipment in the field. We’ll share with you real life examples of the benefits
being generated out of these six types of data utilizing our favorite BI tools:
Excel, PowerPivot, and Power View in combination with the HDInsight platform.
1:15pm – 2:30pm Session 2 – Jen Stirrup MVP
Big Data Visualisation for Business Intelligence Professionals
What does Big Data mean for the Business Intelligence professional?
Microsoft has partnered with HortonWorks to bring Big Data into the hands of
business users via their favorite BI tools: Power View, Power Map, and Power
Query, located in everyone's favourite Business Intelligence tool: Excel.
After the Big Bang explosion of data, how are you going to serve it to business
users to derive value for the enterprise? Data, regardless of its size, is only
valuable if it is understood. In this session, we’ll visualize Big Data in our
favorite BI tools: Excel, PowerPivot, and Power View. Join us to see where the
Microsoft Big Data offering differs from more familiar data visualization
methods from Microsoft and learn how it is applicable to your enterprise.
2:45pm – 4pm – Session 3 – Allan Mitchell MVP
Making the most of your Azure data
Using HDInsight in the cloud, how do you make the most of your data?
This session is going to look at two of arguably the most prevalent and
important tools when looking to gain insights from your data:
Pig. Pig is a platform for analysing large datasets using a high level language.
It was developed in order to avoid the complexities of Map Reduce, and is
therefore easy to use, intuitive and parallel. During this session we will see
Pig being used to manipulate structured and unstructured data, and this is
particularly relevant to people who are familiar with SSIS.
Hive. Hive is often known as data warehousing in Hadoop, but really it is so
much more. It allows one to perform complex and deep manipulation of your data
and is the basis for presentation to analytical tools such as Microsoft Office
365 Excel 2013 and PowerPivot. It uses a language called HiveQL which is similar
to SQL, and is thereby accessible to to all Microsoft Business Intelligence
Once you have finished manipulating your data you are going to want to present
it in some fashion. This is where Microsoft's familiar BI tools come into their
own, allowing us to perform analysis on Hive held data with ease using
everyone's favourite business intelligence tool: Excel.
4:30pm – 5:30pm – Plenary Q&A Session – all speakers from both tracks
Closing summary and open Q&A.