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Data management and integration pull huge amounts of dissimilar data from
various sources and rapidly transports, transforms, cleanses and integrates
them. Srinivasan of Informatica feels that as enterprises take on more
applications, these will be the killer technologies that partners should focus
on today
Acompany flooded with innumerable applications has no time to sit back and
rest when the applications are being processed. Effective synchronization of
data alone can help the applications run without debacle. That is what data
management and integration (DMI) does for an enterprise. The activity of
gathering scattered data from fragmented environments and providing it to users
in a unified way, most importantly in a secured manner, is what is known as data
management. It can be broadly categorized into storage, security and
application, because these are the primary reasons for an enterprise to manage
the data.
There are numerous terms associated with data architecture such as data
model, data governance etc. Data architecture is basically an organization's
ability to categorize data into various elements so that it is available for all
the applications that are there. Besides that, ensuring the availability of data
for intelligent usage such as in business intelligence (BI) and data warehouses
is what data architecture is all about. There are absolutely no restrictions for
data integration in the enterprise data architecture and it can access data from
any resources.
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Srinivasan Country Director, Informatica |
Management & integration
Data management and data integration are complementary technologies and
don't cannibalize each other. The first step, or one of the key essentials for
data management, is data integration. Data management in an enterprise is the
ability to ensure data stewardship or data ownership and the ability to assign
responsibility to ensure that data is available, secured and reliable. In order
to do that it is important that first data is integrated. Informatica offers
data integration and data quality pieces, which are key components of data
management. More information intensive applications use in verticals like
telecom, finance, manufacturing and government are truly in need of DMI
solutions. The volume and need to share existing data in these verticals
eventually explodes, which in turn forces them to go for techniques like DMI and
integration.
Adoption rate
The awareness of DMI among enterprises is not so encouraging. Several
companies are still using old methods to manage and integrate data. They are
mainly using hand coding instead of tools to effectively integrate data.
The global DMI market is moving way ahead of the Indian market and only 15 to
20 percent of enterprises are currently using data integration tools. The global
market is moving ahead of Indian market in terms of using the integration tools.
But the rate of growth in the Indian enterprise is such that the adoption of
data integration tools will considerably increase in 12 to 18 months.
Organizations are feeling the need to use this technology and we have no
doubt about the increase in growth. However, it is very difficult to estimate
the growth rate due to the size of the market. Once players are able to reach
customers and explain the advantages of the emerging tools in the data
integration segment, the scenario may change dramatically in terms of adoption.
Data warehousing
It is often believed that data integration stops with data warehousing. But
this is just a part of data integration, where it provides a common data model
for all data of interest, regardless of the data's source. This makes it easier
to report and analyze information than it would be if multiple data models from
disparate sources were used to retrieve information. Data warehousing is just
one of the applications of data integration. Data migration (moving data from
one application to another application), data combining, data consolidation
(most of the data centers are deploying this to reduce the cost of maintenance)
are the other few applications of data integration.
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Advantages |
- It is platform independent, where any data
working on any source could be integrated.
- Data integration software is built for
mass data sourcing and movement. As data sources multiply, volumes expand
and transformations become more complex, a data integration environment
scales accordingly.
- Data integration software can be quickly
deployed and inherently easy to maintain, as it does not require hand
coding.
- Within a data integration environment,
plug-and-play support for web services enables data integration solutions
to adapt quickly to a company's existing and new web services processes.
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Apart from extracting data, ensuring the quality of that data is most
important. There are several factors for this data integration and data quality
business. It is not just accessing the traditional databases but also looking at
non-traditional sources such as integrating the data captured from process
control systems, which is really a challenging task for the enterprises.
There are few single integration technologies that are available such as
enterprise application integration (EAI), enterprise information integration (EII).
However, these technologies are little different from data integration. EAI
addresses a different need. Though some companies use this methodology, it is
slightly ineffective, in that it only does a particular task. You could say that
data integration is complementary to EAI and EII. One should make customers
aware of this fact. Moreover, DI also marries well with EAI and EII integration
technologies. They can leverage its unique attributes, and vice-versa, in order
to integrate, visualize and track any type of data, in any quantity to and from
any platform, scheduled or event driven, for any enterprise data requirement.
Requirement for data integration
There is a continuous effort to ensure that the integration tools are
getting better. Being an independent vendor we work with partners like SAP,
Oracle, Sun in order to provide them cutting edge technology.
The requirements of the customers must be clearly understood by partners
before deploying solutions. Critically analyzing the requirement of other
components for the effective utilization of data by the intelligence is also a
challenging task. There could be reporting tools, analytical tools apart from
integration tool, which partners must identify accurately.
The need for data integration is apparent in all enterprises irrespective of
their size. It is said that the large enterprises will start deploying data
integration on a larger scale due to the complexity involved in their
organization. As the complexity grows in an organization and a need for central
repository of data is felt. There are immense opportunities for data
integration in those areas and partners can straight away approach clients for
deploying solutions.
These are exciting times for DMI in India. As we increase the awareness by
talking to more partners and enterprises we see an excellent future. Currently
we are at the nascent stage and we can only get better from here.
NR Sethuraman
sethuramannr@cybermedia.co.in Page(s) 1
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