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Business Data
Alignment
‫طاهری‬ ‫مهدی‬ ‫سید‬ ‫دکتر‬
‫مرکزی‬ ‫کتابخانه‬ ‫رییس‬ ‫و‬ ‫علمی‬ ‫هیئت‬ ‫عضو‬
‫طباطبائی‬ ‫عالمه‬ ‫دانشگاه‬
http://www.smtaheri.ir
taherismster@gmail.com

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What is business data?
• is data that is captured and stored by a business as a digital
asset that may support strategy, decision making and day-to-
day operations.
• This includes source data that a business collects and
data that has been processed such as calculated metrics and
forecasts.
• Business data can be stored in databases that are machine-
readable or represented as information intended for human
consumption such as a user interface, document or report.
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The following are common types of
business data.
Audit Trail Customer Data
Dark Data Knowledge
Machine Data Market Research
Master Data Metadata
Metrics Product Catalog
Qualitative Data Quantitative Data
Reference Data Transactional Data
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The following are common examples of
business data
Leads & Opportunities
• Lists of potential customers.
Customer
• Customer details such as name and address.
Transactions
• Records of commercial transactions such as customer purchases.
Interactions
• Records of interactions with customers and other stakeholders such as investors, employees
and the media. For example, records of visits to your website.
Social Media
• Data regarding your target markets or reputation that is collected from social media sources.
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Business Data Repository (BDR)
• A centralized storage facility, such as a proxy server
or file server, where business transactions, contact
information, files and other data is kept. Also called
“Business Data Archive”.
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Business data management
• Business data management is an essential
activity in all types of companies. The four
basic steps in business data management:
Data creation, data storage, data processing,
and data analysis.
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Enterprise data management
• (EDM) is an organization's ability to effectively
create, integrate, disseminate and manage
data for all enterprise applications, processes
and entities requiring timely and accurate data
delivery.
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Data management strategy
• Is the process of planning or creating
strategies/plans for handling the data created,
stored, managed and processed by an
organization.
• It is an IT governance process that aims to create
and implement a well-planned approach in
managing an organization’s data assets.
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The key objective behind data management strategy is to
develop a business strategy that ensures that data is:
• Stored, consumed and processed in a manner required
by the organization
• Controlled, monitored, assured and protected using
data governance and security processes and policies
• Stored, categorized and standardized using defined and
known data classification and quality frameworks
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Business data analysis
• Aims to evaluate whether business data are aligned with
an organization’s goals or not.
• Business data analysis includes the activities to help
managers make strategic decisions, achieve major goals and
solve complex problems, by collecting, analyzing and
reporting the most useful information relevant to
managers' needs. Information could be about the causes of
the current situation, the most likely trends to occur, and
what should be done as a result.
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Business data alignment
• More organizations are aspiring to become ‘data
driven businesses’. But all too often this aim fails, as
business goals and IT & data realities are
misaligned, with IT lagging behind rapidly changing
business needs.
• So how do you get the perfect fit where data
strategy is driven by and underpins business
strategy?
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The main ideas are:
• How to align data strategy with business
motivation and drivers
• Why business & data strategies often become
misaligned & the impact
• Defining the core building blocks of a successful data
strategy
• The role of business and IT
• Success stories in implementing global data strategies
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Data strategy
• Data Strategy describes a “set of choices and decisions that together, chart
a high-level course of action to achieve high-level goals.” This includes
business plans to use information to a competitive advantage and support
enterprise goals.
• A Data Strategy requires an understanding of the data needs inherent in
the Business Strategy:
• “It’s the opportunity to take your existing product line and market it
better, develop it better, use it to improve customer service, or to get a
360-degree understanding of your customer. Data Strategy is driven by
your organization’s overall Business Strategy and business model.
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OR
• A data strategy is a common reference of methods, services,
architectures, usage patterns and procedures for acquiring,
integrating, storing, securing, managing, monitoring, analyzing,
consuming and operationalizing data.
• It is, in effect, a checklist for developing a roadmap toward the
digital transformation journey that companies are actively pursuing
as part of their modernization efforts.
• This includes clarifying the target vision and practical guidance for
achieving that vision, with clearly articulated success criteria and key
performance indicators that can be used to evaluate and rationalize
all subsequent data initiatives.
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A Well-Developed Data Strategy has:
• A strong Data Management vision;
• A strong business case/reason;
• “Guiding principles, values, and management perspectives.”;
• Well-considered goals for the data assets under management;
• Metrics and measurements of success;
• Short-term and long-term program objectives;
• Suitably designed and understood roles and responsibilities;
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Businesses Develop a Data Strategy to:
• Manage torrents of data that are critical to a company’s
success;
• Think of the future and trends and how to best
manage them;
• Drive innovation and establish a data culture;
• Support the re-imaging of decision making in an
organization – at all levels;
• To develop a sustainable competitive advantage given the
volume, depth and accessibility of digital data.
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Four common drivers
• Though the impetus for creating a data strategy
can vary from one organization to the next, there
are four common drivers:
• Unification of business and IT perspectives.
– In this way companies can adopt a “business-
led/technology-enabled” approach for not only
internal operations but also vendor and partner
collaborations.
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• Enterprise-wide alignment of vision and
guidance on leveraging data as an asset;
• Definition of key metrics and success criteria
across the enterprise:
– The data strategy defines “success” and
“quality,” thus reinforcing consistency for how
initiatives are measured, evaluated and tracked
across all levels of interacting organizations;
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• Reduction of technology debt. A data strategy
takes the current state of the enterprise data
environments and operations into account and
provides guidance for applying innovation with
minimal disruption to ongoing business
operations.
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Organizations should include eight
components in their data strategy:
1. Semantics
2. Goals/vision and rationalization
3. Strategic principles
4. Current-state documentation
5. Governance model
6. Data management guidance
7. Reference architecture
8. Sample and starter solution library
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