There are revised patterns available for big data advanced analytical capabilities using the Azure Databricks platforms with Azure Machine Learning.

The new capabilities will enable advance analytics to be carried out using Azure Machine Learning. The different types of data requirements and consumption are integrated using CosmosDB.

Research meets Industry

Academic research and industry have often had siloed approaches. Academic research is essential to drive an industrial innovation. Often this research takes many years and may or may not result in commercial application. Over the last few years universities have been changing their old mind set and presentation, trying to raise the profile of their research and create impact in the community. It is about telling the story of the research and how that impacts society, that is key.

Large organisations in industry are beginning again to have their own research departments. In the last decade we saw the closure of many industry research laboratories as they were seen as a luxury and not fully integrated with businesses. Academic research has often not addressed the individual needs of industry and has, in some cases, not been keeping up with the speed of change in industry. There is a revival of organisations creating research facilities or investing in research and development. Those smaller to medium companies which had research divisions, are also revamping their presence. Competitive advantage can be obtained through the results of innovation.

Artificial Intelligence (AI) brings new challenges to research. Collaboration between big players, such as Microsoft Cortana and Amazon Alexa, aim to drive innovation forward. Once AI starts to be integrated into products and businesses, the insights and intelligence it brings, will begin to shape a new way of creating commercial applications and possibilities for innovation.

The world today is full of complexity and data is the fuel that helps drive intelligent action. Using data science, it helps breach that multi-disciplinary area to benefit all. Businesses must be grounded in accurate data to produce the next industrial revolution, through innovation and AI.

There is a new computational research centre of excellence (CoSeC) in the UK. The centre is bringing together leading UK expertise in key fields of computational research to tackle large-scale scientific software development, maintenance and distribution. This will improve scientific research software, that is relied upon worldwide, by universities and industries.

Thus, having a clear agenda that combines research and industry is the route to successfully navigating the fast moving business landscape.

Articles

So long to the silos 

Breaking Down Silos In Academic Cancer Research 

Systemsnot silos: new industrial strategy must deliver on a bold, long-term vision

The rise and fall of corporate R and D Out of the dusty labs

New R and D Centres: Major funding for new crop science research centre that will be ‘centrepiece‘ of industrial collaboration 

Water Innovation and Research Centre WIRC @Bath 

AlanTuring Institute up and running

ONS looks to big data as it explores new ways to measure UK economy

Microsoft  Research AI (MSR AI)

‘Cortana, Open Alexa,’ Amazon Says. And Microsoft Agrees
New computational research centre of excellence

Free Power BI Designer Desktop App

The new PowerBI dashboard designer in early preview in the US provides data transformation and visual analytics to build reports. It can be downloaded from powerbi.com 

Power BI Designer consolidates Power BI Excel add-in tools: Power Query, Power Pivot and Power View into one application.

Power BI Designer also provides self-service ETL . The free desktop data discovery tool can be downloaded and installed side-by-side with any version of Office or Excel on Windows.

More details are in the great article by Jen Underwood at  http://sqlmag.com/power-bi/introducing-free-power-bi-designer-desktop-app

The use of power BI tools is discussed by James Serra  with tools defined as


•Front-end (Excel) 
•Data shaping and cleanup. Self-service ETL (Power Query) 
•Data analysis (Power Pivot) 
•Visualization and data discovery (Power View, Power Map, Power BI Designer)
• Dashboarding (Power BI Dashboard)
• Publishing and sharing (Power BI sites)
• Natural language query (Power BI Q&A)
• Mobile (Power BI for Mobile)
• Access on-premise data (DMG, Analysis Services Connector) Power Query Power Pivot Power View Power Map Power BI Designer Power BI Dashboard Power BI Site Power BI Q&A Power BI for mobile

James displays the data flow as

http://www.slideshare.net/jamserra/power-bi-made-simple

Microsoft's Modern Data Warehouse

This article “Modernizing” Your Data Warehouse with Microsoft depicts how the new Microsoft data platform stack fits together.  This article also makes reference to The Modern Data Warehouse  paper from The Data Warehousing Institute (TDWI) providing interesting insight into the future of data warehousing. The replacement of data warehouse platforms over the next 3 years will empower organizations in their quest to leverage big data, provide more business insight, integrate platforms and provide scalability. The Microsoft Whitepaper provides further information.

Statistical Analysis for Data Science

To begin learning about Data Analysis and what tools are available understanding terminology is useful.

Data analysis is a body of methods that help to describe facts, detect patterns,
develop explanations, and test hypotheses. It is used in all of the sciences. It
is used in business, in administration, and in policy (Levine, J.H.)

Some of the Data Analysis tools around:

Statistical Analysis with R and Microsoft SQL Server 2012
http://blog.sqltrainer.com/2011/12/statistical-analysis-with-r-and.html

The R Project for Statistical Computing
R is a free software environment for statistical computing and graphics.
http://www.r-project.org/ . R Journal here: http://journal.r-project.org/current.html

RStudio
RStudio IDE is a powerful and productive user interface for R. 
http://www.rstudio.com/

R tutorial

Introductory tutorials for R which simplify many statistical computations and can be a powerful tool.  http://www.cyclismo.org/tutorial/R/

10 R Packages Every Data Scientist Should Know About
http://blog.yhathq.com/posts/10-R-packages-I-wish-I-knew-about-earlier.html

    sqldf (for selecting from data frames using SQL)
    forecast (for easy forecasting of time series)
    plyr (data aggregation)
    stringr (string manipulation)
    Database connection packages RPostgreSQL, RMYSQL, RMongo, RODBC, RSQLite
    lubridate (time and date manipulation)
    ggplot2 (data visulization)
    qcc (statistical quality control and QC charts)
    reshape2 (data restructuring)
    randomForest (random forest predictive models)

MSBI Academy
http://msbiacademy.com/
Learn Microsoft's BI software with an expert, using a library of free instructional videos. Topics cover the full range of Microsoft BI technologies from Data Modeling to Dashboard Design.