The only thing that will stop data silo is strong and effective governance
Although data is life blood of digital enterprise today,
very few organizations can manage their data effectively, most of them are
inundated with overwhelming data flow, from small data to large data set to monolithic
data silos, from esoteric data definitions to rigid data process. In order to figure
out better data management solution, the first step might be to ask: What
causes islands of disparate data? The key reason can be classified into:
1. Data Governance -Principles/Policies/Processes
What causes data isolation? The most common causes is lack
of data governance disciplines which include bad planning, lack of basic data
principles, disciplines, procedures, standards, inconsistent data management
policies/oversight/governance. In larger corporations, the teams building
solutions simply don't know that data is already governed by the enterprise.
Without a comprehensive metadata strategy, how would they know what data
standards exist or where identical data is stored?
What causes islands
of redundant, disparate data? It’s a 'project driven' data strategy.
Project Managers and project teams are under extreme pressure to implement a
given solution as quickly as possible and expending the least amount of money
possible. In the absence of a strong governance framework, they'll look at what
data they require to implement their own project and deem it easiest/quickest
to create a database with all their needed data in their own domain and write
their application directly against it. So, it causes data redundancy, bad data quality, data silo or unnecessary complexity, then the
islands of disparate data are formed.
2. Data Stewardship
Lack of data ownership is the other lead cause. In some
cases, it’s the abandonment of data ownership. Usually IT plays such data steward
role, but steward is not necessarily as ownership, it takes cross-functional
collaboration to breakdown silo and manage data seamlessly.
How many
organizations focus on data stewardship? There are generally no attempts to
gather and hold knowledge on the how-what-where-who of data in an organization.
It would be nice to have a data ‘guru’ or team of data experts, well mixing data
architects or other technical roles, to guide the answers to the key
questions:
What data is needed?
Where is the data?
Who owns it?
How do we get it?
What data is needed?
Where is the data?
Who owns it?
How do we get it?
…
The tension between
centralization vs. decentralization: Every large corporation has tension in
it, between the forces for centralization and those for decentralization. This
is as old as the hills. Those in the center can come up with the strategies,
but are incapable of delivering the solutions to the business units; those
attached to the business users can deliver tactical solutions, but aren't
interested in the big picture. So the challenge is to meet the demands of
business units while coordinating the disparate silos of development where
possibly providing achievable enterprise-wide solutions.
3. Finance
The other cause of ‘Island
of data’ is finance related. Most large companies assign budgets on a
departmental basis, as they set up functional goals. In such cases, departmental managers
are only interested in meeting their own goals and in many cases will only
finance IT projects that further those departmental goals. So there’s no unified IT budget for data management or try
to maximize ROI by sub projects, it all causes the issues to manage data
efficiently and effectively cross-enterprise scope..
The organizations have
built up these data islands over years of effort and they aren't torn down over
night. The only thing that will stop that is strong and effective governance. Data Classification and strong governance can turn the tide though and
set you on the right path.
1 comments:
What to think about promoting running IT like a factory. With the limitation of being capable delivering any color of that as long it is black.
The analysts/users needing an IT product that is assembled by choosing from a lot possible options as needing for a area of dedicated goals.
This big hole in expectations is a big cause of all islands of data being spread arround.
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