The digital-first business climate brings with
it more data sources than ever before. While the astronomical increase of
accessible data is a welcome one, it presents new data management challenges and implications.
This is because the more data we accrue, the harder the data is to collect,
standardize, interpet, and trust.
Metadata management plays a critical role in
maximizing the value of data. It ensures data consistency, governance, and
compliance while providing the contextual information needed to make educated
business decisions.
Image source - Unsplash
This article is going to explore the benefits
of metadata management and some key best practices. But first, what exactly is
metadata?
What is Metadata?
We can understand metadata by thinking of it
as data that describes other data. If an Excel file is your primary asset, then
any information about that asset - for example, its size, content tags, location,
or user restrictions - is referred to as the asset's metadata.
We interact with metadata every single day.
Think of the nutritional information on the back of a cereal box, or the page
in your favorite novel that details the publication date, ISBN, copyright info,
etc. This data is there to provide us with additional, contextual information
about the product itself.
In fact, ‘meta' is a prefix that means
"an underlying definition or description." Metadata is simply that, a
summary of the data we've collected that makes organizing and interpreting the
data much more efficient.
What is Metadata Management?
Metadata management, often referred to as
enterprise metadata management (EMM) is the practice of organizing,
classifying, and standardizing data across your entire business ecosystem.
Think, for example, of your machine learning
pipeline. The only way to fully codify, automate, and deploy a successful
machine learning model is to have end-to-end visibility of your raw data
inputs, outputs, and data predictions. This data needs to be easily-accessible
across your business and compatible with other systems.
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One of the most crucial ML pipeline best practices is to implement
pipeline-related metadata management. This enables you to meticulously organize
all of this data to improve its quality, interoperability, and reusability.
Types of Metadata
Metadata can be categorized into various types
depending on its purpose. The three main types of metadata are administrative,
structural, and descriptive.
Administrative
This type of metadata presents the technical
and administrative information about an asset. It's one of the most critical
types of metadata to possess because of its value to data governance,
compliance, and data management procedures.
Examples of administrative data include file
size and location, access permissions, archiving requirements, and creation
dates.
Structural
Structural metadata describes how an asset is
organized and formatted. Beyond giving us contextual information about the
asset's internal structure, structural metadata can be used to determine the
interoperability of data and its relationship with other assets.
Examples of structural metadata include a
table of contents, page numbers, indexes, and chapters.
Descriptive
Descriptive metadata is the most robust of all
metadata types. It defines the descriptive information of an asset so that it
is easier to discover and identify. Descriptive metadata is essential for
cataloging assets like books and documents.
Examples of metadata for a book would include
its title, author, genre, publication date, and keywords.
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Other types of metadata include:
- Process metadata: information
relating to the procedures used to manage statistical data, e.g. audit results
and error logs.
- Preservation metadata: concerned
with information that enables long-term maintenance and preservation of an
asset, e.g. rights management.
- Provenance metadata : the
information relating to the movement and modifications of an asset, e.g.
duplications, change logs, ownerships
- Usage metadata: defines how a data
has been used, e.g. access patterns and comments
8 Benefits of Metadata Management
Let's discuss some of the benefits of metadata
management and why it's become essential in the data-driven business climate.
1.
Enhanced Data Quality and
Searchability
Not only do metadata management solutions
provide detailed metadata and data lineage, but they leverage automation to
classify, standardize, and corroborate data. This means that all data
inconsistencies and issues are rectified in real-time, decreasing the potential
of human error and improving the quality of data.
An added benefit of real-time automation is
that employees can receive the most up-to-date data, thus improving data
quality and the success of using said data to make pivotal, on-trend business
decisions.
2.
Quicker Access to Insights
Just as autoML
tools allow you to automate the application of machine learning to
real-world problems, metadata management platforms accelerate the generation of
actionable insights by providing you with an automatically structured and centralized
storage system.
Businesses often have to navigate various
complex systems just to collect and unify data. In fact, a huge 60% of data scientists' time is spent on data
cleaning and organization.
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Metadata management solutions allow data
handlers to spend less time cleansing, collecting, and organizing data, and
more time applying it to real-world scenarios.
3.
Improved Data Consistency
In a managed metadata environment (MME), all
data is standardized to eliminate the potential of error caused by conflicting
terms. Formats, languages, and other attributes are labeled and transformed
according to an internally compatible schema, eliminating data inconsistencies
across integrated data sources.
Better data consistency makes data easier to
retrieve and navigate, improving the time it takes to apply data to projects.
4.
Reduced Costs
Automated and repeatable metadata management
solutions don't just save you time - they also save you money. As a data trend that promotes sustainability,
metadata management solutions lower storage costs and facilitate better
resource cost estimations, effectively reducing redundancy and excess
expenditures.
5.
Optimized Marketing Strategies
Marketers are cleverly using metadata to
monitor content usage. By tracking customers across data sources, they can
gather metadata that gives context to these interactions, in turn enhancing
their on-page marketing strategies and increasing sales. A common example of
this is the ‘people who bought this item also bought' section that you see on
plenty of ecommerce websites.
Metadata management can also enhance customer
retention strategies. Say, for example,
you're using software to start referral program marketing.
While you could simply approach each customer with the same referral template,
you'll have much more success by personalizing your campaigns.
Most referral program software allows you to
add custom attributes to your campaigns. Along with basic information like
name, gender, and age, you might also collect keywords, buying frequency,
acquisition channel, payment method, and more.
6.
Better Data Governance, Compliance
and Security
Poorly organized data is vulnerable to
compliance issues, cyberattacks, and data breaches, all of which can have
serious financial, reputational, and even legal repercussions. According to IBM research, the average cost of a data
breach exceeds $3m.
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Metadata management solutions automatically
identify, catalog, define, and standardize sensitive data like personally
identifiable information or financial details. This sensitive data is flagged,
making it easier to secure and govern in compliance with regulations like GDPR,
HIPAA, and CCPA.
Armed with automatic sensitive data
classification, businesses can exert more control over sensitive data by
creating security filters, user restrictions, and other measures. It also
increases internal visibility of how sensitive data is being used across workflows.
7.
Improved Talent, Productivity, and
Employee Satisfaction.
Metadata assists in our ability to source
high-quality talent, achieve ultimate software diversity and inclusion,
optimize internal workflows, and foster positive working environments.
Employees that are more satisfied are more engaged and productive, resulting in
the increased generation of innovative, actionable ideas and implementations.
8.
Drives Digital Transformation
Digital transformation is well and truly upon
us, with 89% of companies adopting or planning to adopt
a digital-first business strategy.
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Whether it's investing in a financial systems modernization solution to
facilitate digital banking or simply creating a smarter mobile app experience,
businesses are utilizing the likes of artificial intelligence, advanced
analytics, and Internet of Things (IoT) to lead their digital transformation
endeavors.
What does this have to do with metadata
management? Well, to execute enterprise-level digital transformation projects,
you need data - and lots of it.
A huge benefit of metadata management is that
it provides you with a full-scale view of your data landscape. Automation
enriches your digital operations by enabling the speedy retrieval of
high-quality data, in turn speeding up data analysis and implementation
processes.
Metadata management also drives digital
transformation and innovation by evidencing how customers interact with your
digital experiences. It assists the optimization and personalization of your
customer journey, helping to build digital ecosystems that align with customer
preferences.
Key Best Practices For Metadata
Management
Now you know the benefits of metadata
management, it's time to explore how to actually implement it. The planning and
execution of metadata management varies across businesses and industries, but
there are some key best practices that you should follow to promote
sustainability.
Define Your Metadata Strategy
The long-term value of your metadata depends
upon a clearly defined and unified metadata strategy. Your data management
goals should align with your business' needs and objectives, and should also
identify the foundational talent, tools, and processes that you need for
successful execution.
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Metadata strategies provide a clear direction
for your initiatives. Your answers to the questions below should help you form
a foundational metadata strategy that you can build upon as you analyze the
intricacies of your unique business goals.
- What types of metadata do you
require?
- What types of metadata might you
require in the future?
- What current or future issues will
be solved by investing in metadata management?
- Where is the metadata located?
- What obstacles might you arrive at
when it comes to obtaining metadata?
- What are your current and
prospective use cases for metadata?
Identifying the use cases for metadata and
which of them you should prioritize is of critical importance as it guides the
overall trajectory of your initiative. While it's a best practice to leverage
all types of metadata, consider whether you'll prioritize improving data
quality, data orchestration, governance, or something
else.
From there, you can specify exactly how you'll
utilize metadata across integrations, departments, publications, and more.
Leverage The Right Tools
With so many metadata management tools to
choose from, how do you know which ones are right for you?
The best metadata management tools combine
machine learning and AI with data analytics integrations to provide you with
intricate data context. Not only should the tool provide you with the different
types of metadata (structural, administrative, descriptive, etc), but it should
increase discoverability across all of your data sources, from your data lakes
to your flat files.
Speaking of data lakes, ensure that you have
an advanced data lake storage solution like Azure data lake. What is Azure data lake? It's a cloud-native
platform that supplies a centralized repository combined with augmented
security facilities, data authentications, and the ability to handle
large-scale queries.
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Consider the integrability of your tools and
data sources too, along with how efficient they are at capturing data. For
example, docusign enterprise pricing solutions are more
likely to have better integration and metadata extraction capabilities than
free plans.
Adopt Metadata Standards
Metadata standards establish data uniformity,
standardizing your vocabularies, formats, schemas, etc. to provide
interoperability between your systems. Without a metadata standard, you risk
system incompatibility and decrease your data's accessibility which, in turn,
decreases data value and productivity.
The metadata standard you choose may depend on
your specific industry or how straightforward/complex your goals are. The most
common metadata standard for general use is the Dublin Core Metadata Element Set. Other
industry-specific metadata standards include the Text Encoding Initiative
Guidelines (TEI) and the ISO 19115 standard.
Conclusion
Metadata might exist behind-the-scenes, but it
plays a vital role in how successfully we extract value from data and apply this value
to real-world issues.
Metadata management supports businesses as
they strive to continuously meet changing customer demands. For businesses who
pride themselves on being the customer orientation definition, metadata
management enables them to orient their products, marketing messages, and
customer service strategies to align with what the customer wants.
Implementing a metadata management strategy
cultivates a data-driven culture and drives collaboration, innovation, and the
generation of increasingly intelligent business decisions.
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ABOUT
THE AUTHOR
Pohan Lin - Senior Web
Marketing and Localizations Manager
Pohan Lin is the Senior Web Marketing and Localizations
Manager at Databricks, a global Data and AI provider connecting the features of
data warehouses and data lakes to create lakehouse architecture. With over 18
years of experience in dynamic gaming
solutions, web marketing, online SaaS business, and ecommerce growth. Pohan is
passionate about innovation and is dedicated to communicating the significant
impact data has in marketing. Pohan Lin also published articles for domains such
as SME-News. Here is Pohan's LinkedIn.