Few of the areas I have worked in past are  :

                        Big Data                                                     Analytics                             Data Warehouse

              ATM Cloud-era data lake                            ATM Cash Forecasting                   Telecom EDW

              Big Data as a Service                                   Real Time Cross Selling                 Banking DWH

              Fintech Azure Data Lake                             Face Recognition                            Retail EDW

              Banking Fast Data Platform                        Loan Defaulter                              

It is exciting to work on various big data and analytics area with End to End solution on Big Data.

Cloud Project Management

Points to consider when managing a Cloud Project :

1. Cloud computing should not be a set of independent, incompatible solutions
2. Cloud computing is more complex and will have a different balance of project constraints.
3. Clouds need to be designed and managed as an ecosystem and this touches on virtually all areas of the IT department;
4. Cloud computing, even though based on previous technologies, is not yet well understood and widely taught.
5. Cloud computing is a partnership with one or more external vendors – well-defined performance requirements, service level agreements, and possibly multiple procurements will be required; and
6. Operations staff have relatively little training or experience with managing cloud systems.

Exadata

Recently worked on a project which involved Exadata DB Machines. It was about moving terabytes of data to exadata. The database machine and its features was a good use for high volume of data.

Introducing an Exadata Database Machine into an existing environment involves, for most IT organizations, adoption of several technologies that may not be familiar.  Some of these technologies include:

Oracle 11gR2

Real Application Clusters

Automatic Storage Management

Exadata storage

Enterprise Linux

InfiniBand networking

Some features which we used :

Hybrid Columnar Compression

Compressing data can provide dramatic reduction in the storage consumed for large databases. Exadata provides a very advanced compression capability called Hybrid Columnar Compression (HCC).

Average storage savings can range from 10x to 15x depending on how HCC is used.  With average savings of 10x IT managers can drastically reduce and often eliminate their need to purchase new storage for several years.

Smart Scan Predicate Filtering :

Exadata enables predicate filtering for table scans. Only the rows requested are returned to the
database server rather than all rows in a table. For example, when the following SQL is issued
only rows where the employees’ hire date is after the specified date are sent from Exadata to the
database instance.
SELECT * FROM employee_table WHERE hire_date > ‘1-Jan-2003’;
This ability to return only relevant rows to the server will greatly improve database performance.
This performance enhancement also applies as queries become more complicated, so the same
benefits also apply to complex queries, including those with subqueries.

  

Trends in data warehouse in 2012 - 2015 :
Data warehouse is a key component of the IT department and as the demand for business intelligence (BI) and the wider category of business analytic s increases, optimization, flexible designs and alternative strategies will become more important

There are different variants in the market to cater this need :
From In Memory database to open source database and providing data warehouse on the cloud as SaaS.

The term BIG DATA is also common in the IT space which can give organizations a peek into the user activity on the website.


ODI configuration for Big data :
Lets take a look at how ODI is configured for using HIVE and HADOOP.

OBIEE on Cloud :
The features in OBIEE which make is popular product on cloud