Monday, March 9, 2015
Enterprise Developer sessions at Google I O 2010
If you didnt attend Google I/O 2010 you can see the videos of every session on YouTube. All of the Enterprise sessions are now online. See the link at the bottom of this post. Over the next week every session from every track will be available. Check out the Google I/O site for a complete list of session abstracts and videos.
There was a big focus on developing software for businesses at Google I/O this year, centered around three themes: build and sell apps in the Marketplace, customize and extend Googles apps, and build your own apps for internal use. The news kicked off the day before Google I/O with the announcement of Gmail contextual gadgets and many enhancements for Google Apps Script, including JDBC support. Then during the keynote, we launched Google App Engine for Business and announced our collaboration with VMware, and continued with the announcement of Google Wave (Labs) availability in Google Apps and Exchange support in Android 2.2 (aka Froyo).
Altogether there were more than a dozen technical sessions focused on the enterprise and more than 20 Google Apps Marketplace vendors demoing in the Enterprise Developer Sandbox.
Here’s a recap of a few of the sessions below. You can find the videos and slides for these sessions on the linked session title:
- Scripting Google Apps for business process automation - Google’s Evin Levey showed off the latest developments from Google Apps Script, and explained how developers can use the tool to automate business processes.
- Reach new customers fast: Learn how to sell your cloud app on the Google Apps Marketplace - Google’s Scott McMullan was joined by Jay Simmons (Atlassian), Chuck Dietrich (SlideRocket) and Amit Kulkarni (Manymoon) to discuss best practices for launching an app in the Google Apps Marketplace. This session was followed by a technical overview of how developers integrate apps with the Marketplace.
- Building context-aware extensions for Gmail - Deep dive on Gmail contextual gadgets - Google recently launched Gmail contextual gadgets, allowing developers to intelligently surface their apps directly in the Gmail message UI based on the content of the message. In this session, Dan Holevoet of Google explained how to create and distribute these gadgets.
- Run corporate applications on Google App Engine? Yes we do. Google CIO Ben Fried and his team discussed how Google runs real-world business applications on App Engine, and gave practical advice on how enterprise IT developers can make App Engine work with firewalls, legacy systems and proprietary systems. We unveiled this video yesterday along with the rest of the App Engine videos, but are reiterating it here as this session is quite relevant to the enterprise.
- Making Freemium work - converting free users to paying customers - In this panel moderated by Google’s Don Dodge, venture capitalists Brad Feld, Dave McClure, Jeff Clavier, Matt Holleran and Joe Kraus discussed strategies for building free products that can be upgraded to paid versions.
We’re excited to see the great strides our enterprise developer community has made, and were looking forward to seeing even more innovation and progress at next year’s I/O. We hope to see you then!
Monday, February 16, 2015
Part I data warehousing Star schema from orcle documentation
Few of the other basic concepts will be included in Part-II to Part -V
Schema
A schema is a collection of database objects, including tables, views, indexes, and synonyms.
Schema models are used for designing data warehousing.
The Star schema
- It is the simplest data warehouse schema.
- Why it is called star schema ?
Bz the diagram of star schema resembles as a star with points radiating from a center. - The center of the star consists of one or more fact tables and the points of the star are the dimension tables.
- A star schema is characterized by one or more very large fact tables that contain the primary information in the data warehouse and a number of much smaller dimension tables (or lookup tables).
- Each dimension tables contains information about the entries for a particular attribute in the fact table.
- A star query is a join between a fact table and a number of lookup tables.
- Each lookup table is joined to the fact table using a primary-key to foreign-key join, but the lookup tables are not joined to each other.
- A star join is a primary-key to foreign-key join of the dimension tables to a fact table.
- The fact table normally has a concatenated index on the key columns to facilitate this type of join.
Advantages of Star Schema:
* Star schemas are denormalized
* That is ,the normal rules of normalization applied to transactional relational databases are relaxed during star schema design and implementation.
- Simpler queries:
- Star schema join logic is generally simpler than the join logic required to retrieve data from a highly normalized transactional schemas.
- Simplified business reporting logic
- when compared to highly normalized schemas, the star schema simplifies common business reporting logic, such as period-over-period and as-of reporting.
- Query performance gains
- star schemas can provide performance enhancements for read-only reporting applications when compared to highly normalized schemas.
- Fast aggregations
- The simpler queries against a star schema can result in improved performance for aggregation operations.
- Feeding cubes
- star schemas are used by all OLAP systems to build proprietary OLAP cubes efficiently.
- most major OLAP systems provide a ROLAP mode of operation which can use a star schema directly as a source without building a proprietary cube structure.
References:
http://docs.oracle.com/cd/A87860_01/doc/server.817/a76994/schemas.htm
http://en.wikipedia.org/wiki/Star_schema