DATA in the central database. They can integrate the

DATA
WAREHOUSE

 

History

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Data has begun to proliferate during the 70’s and 80’s
so there is a need for the organizations to have an easy way to store and
access the data/information. Bill Inmon is considered as the father of data
warehousing as he was the first to coin the term and define the concepts in
1970. His book “Building the Data Warehouse” is considered as the fundamental
source for warehousing during the year 1992. According to Inmon, centralized
repository is established first and within the repository, data marts which
contain specific subsets of data are created so his definition of warehouse is
called top-down approach. Later in 1992 Ralph Kimball suggested a slightly
different tactic to data warehousing concept with his bottom-top approach,
where individual marts are developed first and are integrated together to
create a data warehouse. 1

Importance

To make informed decisions organizations need data so,
this makes the concept of data warehouses an important topic because they store
all that data. Data warehouses can store large amount of data in the standard
format in the central database. They can integrate the data from different
sources and standardize the data which is helpful for analytics/reporting. They
maintain the data in a single location, so the data stored is secured and can
be accessed to those who need specific data. They provide quick access which
will help in improving the business decisions.

Tools

There are many tools that help the companies to meet
their comprehensive needs. Some of the examples of data warehouse tools that are
available in the market are Ab Initio software, Amazon red lift, analytiX DS,
Code futures, datallegro, holistic data management, informatica corporation,
paraccel, Teradata corporation, bime, vertica, profit base, net app, keboola,
kalido, Greenplum, Netezza, pervasive, SAP business warehouse, hyperion,
numetic, alteryx, talend, mark logic, Par Accel, IBM infosphere, informatica. As
there are many tools available in the market, there is a need for the companies
to choose a proper tool based on their requirements which help them to grow.
Having number of options in the market also lays stress over the importance of
proper analysis. As the data warehouse being the central repository, it is very
important for every organization to choose the correct tool. 2

 Some of the
companies that are using amazon redlift (data warehouse tools) are financial
times, nokia, vivaki, foursquare, Zalora, commercialize tv, everything me, viki,
redmart, pocketmath.

Future

Earlier companies used to use spreadsheets
to manage the data but now due to big data revolution there has been many
changes on how companies collect, store, manage and analyze the data. Many
advances in data warehousing have helped the companies to take rows of
different bits of information and generate insights to make smarter decisions.
In the last few years size of open database has grown approximately double its
magnitude which clearly shows its significance. And as the size of databases
grow the estimates of what constitutes a large database continuous to grow.

 

Trends

The internet of things and other sources are
generating large amount of data everyday which is termed as fire hose of data.
IT departments in various companies are responding to this situation by adding
new features and capabilities to data ware houses so that they can add new
types of data and perform faster than ever. Many companies have started using
physical and logical consolidation to help reduce cost. Open source Hadoop and
parallel Map Reduce paradigm are used at processing very large data sets. Today most of the data warehouse
managers are using Hadoop to decrease the level of workloads. Customer
service strategies are used in     the
companies where they collect customer information which helps them in sentiment
analysis, sales, customer service, automation, marketing, etc.

 For large scale
information management new generation companies are using engineering systems which
help them to preconfigure and optimize specific kinds of workload. These
systems deliver the highest level of performance without integration problems.
In memory technologies can process large data sets in the RAM which helps in accelerating
the report

Advanced compression methods such as Oracle’s hybrid
columnar are used by companies to capture and store more valuable data.

These latest trends are making the data warehouses bigger
and faster than the former and these trends help in transforming data into
actionable insights with great speed and accuracy. 3

Benefits

A company can benefit in many ways by implementing the
data warehouses into business intelligence plans. Many companies are using data
warehouse instead of direct access because they can integrate many data sources
in real time which will help in making better decisions. This helps in saving a
lot of time for the companies. These are mainly used for making strategic decisions
and also help in making finance and inventory management.

References

1.     SAS.
@SAS Institute Inc. (2016). Data warehouse, what is it and why it matters.
Retrieved from

https://www.sas.com/en_us/insights/data-management/data-warehouse.html#

2.     Jesal
Shethna. (2016, March 2). EDUCBA. 10 popular data warehouse tools and
technologies. Retrieved from https://www.educba.com/10-popular-data-warehouse-tools/

3.     ForbesBrandVoice.
(2017, Dec 8). Forbes. Tech. The top 10 trends in Data warehouse. Retrieved
from

https://www.forbes.com/sites/oracle/2014/03/10/the-top-10-trends-in-data-warehousing/#13df9b761373