Please send matching profile only to st...@dwlabs.com
Need Oracle Data warehouse DBA
Location : Columbus-Indiana
Duration : Long term
Skills:
Lead Oracle Database operations activities, schedule the work and
communicate to BI/DW project managers, Development team & Support teams.
Standardize & automate the process and Prepare standard documents
ETL developers make source data available to the warehouse. Using either
in-house developed or off-the-shelf tools, ETL developers ensure the
warehouse is populated with timely and accurate data.
Very large databases (VLDB) - Oracle DBA partitioning skills, administration
and management of a large database with an analytical front-end
Online analytical processing (OLAP) - Star schema design and DBA
administration
Responsible for the Database objects and performance of a data warehouse.
DBAs are skilled in data administration, data modeling and tuning, ensuring
development teams have the optimum environment in which to deliver
applications.
Materialized Views -The Oracles materialized views (MV) feature uses Oracle
replication to allow you to pre-summarize and pre-join tables. Best of all,
Oracle MVs are integrated with the Oracle 10g query re-write facility, so
that any queries that might benefit from the pre-summarization will be
automatically rewritten to reference the aggregate view, thereby avoiding a
very expensive (and unnecessary) large-table-full-table scan. The Oracle10g
dbms_advisor utility will automatically detect and recommend MV definitions,
then create a materialized view to reduce disk I/O.
Database tuning skills. Use utilities ADDM, AWR, Statspack
Automated Workload Repository -The AWR is a critical component for data
warehouse predictive tools such as the dbms_advisor package. AWR allows you
to run time-series reports of SQL access paths and intelligently create the
most efficient materialized views for your warehouse. The AWR provides a
time-series component of warehouse tuning that is critical for the
identification of materialized views and holistic warehouse tuning. The most
important data warehouse tracking with AWR includes tracking
large-table-full-table scans, hash joins (which might be replaced with STAR
joins), and tracking RAM usage within the pga_aggregate_target region.
Multiple Blocksizes- All data warehouse indexes that are accessed via range
scans and Oracle objects that must be accessed via full-table, or
full-index, scans should be in a 32k blocksize.
STAR query optimization -The Oracle 10g STAR query features make it easy to
make complex DSS queries run at super-fast speeds.
Multi-level partitioning of tables and indexes , Oracle now has multi-level
intelligent partitioning methods that allow Oracle to store data in a
precise scheme. By controlling where data is stored on disk, Oracle10g SQL
can reduce the disk I/O required to service any query.
Asynchronous Change Data Capture
Change data capture allows incremental extraction, so only changed data to
be extracted easily. For example, if a data warehouse extracts data from an
operational system on a weekly basis, then the data warehouse requires only
the data that has changed since the last extraction (that is, the data that
has been modified in the past seven days).
Oracle Streams- Streams-based feed mechanisms can capture the necessary data
changes from the operational database and send it to the destination data
warehouse. The use of redo information by the streams capture process avoids
unnecessary overhead on the production database.
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