Windows 8

I decided to upgrade my desktop to 64 bit version of Windows 8. It was running 32bit Windows XP. I rarely use my desktop. But the other day I poked around and broke something. So, I though I would just upgrade the OS. I walked in to the local Staples from work and picked $69 Windows 8 Pro. It comes with two CDs. One for 32 bit version and another one for 64 bit version. I think this was the smoothest installation ever.

First I upgraded from XP 32bit to Windows 8 32bit. I entered the product key and the installer took care of the rest. The whole thing took about 90 minutes. Next, I booted from 64bit CD and changed OS from 32 bit to 64 bit. Again, all I did was keying in the product key. The installer ran for about 60 minutes. Next thing was setting up my WiFi connection. That's it! I was ready for driving Windows 8!!

I saw some negative comment on the look and feel of Windows 8. But, I am liking Windows 8. I don't have a touch screen. I think the experience will great with the touch screen.

Only one complication I have noticed so far is that I am unable to use Office Outlook web. I can login but I am unable to click on the mails. Well, I shall work on it another day.

Comparison of Netezza, Vertica and Greenplum

.		Netezza(IBM)	Green Plum (EMC)	Vertica(HP)
.	URL	www.netezza.com	www.greenplum.com	www.vertica.com
.	Architecture	MPP	MPP	MPP
.	Data Storage	Row	Column	Column
.	supports SQL	Yes	Yes	Yes
.	Supports Postgrace SQL	Yes	Yes
.	supports JDBC	Yes	Yes	Yes
.	supports ODBC	Yes	Yes	Yes
.	Supports Map Reduce		Yes
.	OS	Red Hat Linux	Solaris	Linux
.	Processor	Netezza Proprietary	AMD Opteron(Sun Fire X4500)	Intel
.	Memory			HP Blade
.	Disk		SATA	Proliant
.	Network		Gigabit Switches
.	Hardware			HP BladeSystem

Inmon vs. Kimball

Inmon and Kimball are two influential data warehousing experts who have shaped the design philosophies of current data warehouses. Though there are similarities, there some fundamental differences. I have tried to document the differences here.

.		Inmon	Kimball
.		Bus Architecture	Hub and Spoke Architecture
.
.		Top down approach	Bottom up approach
.
.	Design Approach	Large centralized enterprise-wide data warehouse, followed by several satellite databases	Several data marts that serve the analytical needs of departments, followed by “virtually” integrating these data marts for consistency.
.
.	Data Structure	Relational-model (third normal form: 3NF)	Multi-dimension model (star-schema and snowflakes).
.
.	Granularity of data	Most granular level possible and must include all the possible historical data within an enterprise.

The three Vs of Big Data.

While talking about Big Data, we always thing about the “Big”(Volume) part. But we should also think about velocity and variety of data to get the complete picture of data.

Volume

  Size of dataset (Terabytes/Petabytes)

   Number of counting records, transactions, tables, or files.

Variety

  Structured

  Unstructured

  Semi Structured

  All of the above.

Velocity

  Batch

  Real Time

  Near Time

  Streams

Hype Cycle of Emerging Technologies

I came across this very interesting chart on hype cycle on a paper from Gartner.

Future of Data Warehousing

Architecture of data warehouses has been relatively stable. But this may changes soon according to a recent article in twdi. Various disruptive technologies may be a contributing factor to this change. Here is a very standard EDW pattern commonly seen in enterprises.

Buzz around Big data

Buzz around Big data is getting louder and louder these days. I found a succinct definition of Big Data from a research paper published from McKinsey Global Institute:

“Big data” refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze.

Data sets are becoming bigger and bigger and the same time it is becoming cheaper to store data. I can relate to some of it. Quite a few years ago my desktop had only 540MB of disk space. This year, I bought a 1TB disk for my desktop. Interestingly, I am filling up my new disk quickly with all the video files I am downloading from camcorder and camera.

With sensors collecting zillions of data, millions of social network users sharing humongous volume of data, “big data” is very close to home. So, what was a subject of discussion in research labs is quite main stream now. But storing the data is only one challenge. If we don’t have the right tool to analyze big data sets, we may not get the value out of it.

Although, all sectors are poised to gain from application of Big Data, Some sectors may benefit more from the rest of the industry. Retail, Healthcare and Government sectors are predicted to reap the benefit of utilizing Big Data.

Business Intelligence tools

Business Intelligence is how we convert data to intelligence. I was looking at a few BI tools. Here are some details:

SAP Crystal Reports

• Connect to virtually any data source, design and format interactive reports, and share them internally or externally.

SAP BusinessObjects Analysis, edition for OLAP

• Perform analysis of multi-dimensional data sets using this OLAP tool designed for financial and business analysts.

SAP BusinessObjects Analysis, edition for Microsoft

• Perform advanced analysis of data residing in your business warehouse (BW) using an intuitive UI within your Microsoft Office environment.

SAP BusinessObjects Web Intelligence

• Perform ad hoc queries and intuitive analysis across heterogeneous data sources online or offline.

SAP BusinessObjects Predictive Analysis

• Mine your information assets to predict future trends.

Oracle Business Intelligence Enterprise Edition 11g (OBIEE)

• Oracle’s comprehensive business intelligence platform that delivers a full range of analytic and reporting capabilities.

SAS Enterprise Business Intelligence

• Provides a complete portfolio of business intelligence capabilities and applies the power of SAS Analytics and Data Integration to create a complete and easy-to-use business intelligence solution.

SAS Office Analytics

· Delivers the robust power of SAS Analytics in a familiar Microsoft Office interface, promoting collaboration and self-service analytics reporting for business users.

SAS Visual Analytics

· Lets you explore big data using in-memory capabilities to better understand all of your data, discover new patterns and publish reports to the Web and iPad^®.

SAS Visual BI

· Offers dynamic and interactive business visualization that lets business users visually explore ideas and information.

MicroStrategy 9

• MicroStrategy Mobile extends MicroStrategy 9 software platform to mobile devices quickly and easily, and provides intuitive business intelligence that is optimized for the mobile user.

QlikView

• Self service BI tool

Tableau 7.0

• Interactive data visualization tool.

Arcplan Enterprise

• Business intelligence reporting and analytics platform.
• Flexible software for creation of BI applications such as reports, dashboards, ad-hoc analyses, forecasts, etc.

IBM Cognos

• Allows you to do reporting, analysis, scorecards, dashboards
• Provides support for mobile access, statistics, collaborative business intelligence

Panorama Necto

• Socially-enabled Business Intelligence solution

Panorama NovaView

• Web-based Business Intelligence product suite that span BI functionality including analytics, reporting, dashboarding, scorecarding and advanced visualization.

WebFOCUS Business Intelligence

• Dashboards and scorecards
• Query and analysis tools and ad hoc reporting
• Mobile BI, Guided ad hoc reporting