| Course
Duration |
: Data
Cataloguing Fundamentals for Business and
Technology Professionals |
| Course
Duration |
: 2 Day
Workshop Face-to-Face Instructor-led Workshop
- Classroom
: Online
workshop are delivered in two days, two units
each day between 9:15 am to 1 pm and 2:30 pm
to 5:30 pm |
| Course Fee |
: Available
upon request (Write to us at info@tlcpak.com) |
| Course
Location |
: TLC
(Karachi), Customer Onsite and Online |
| Course Code |
: TN209 |
| Deliverables |
:
Comprehensive Student Guide and Workshop
Certificate |
Customer onsite
workshop can also be conducted for customers in
Lahore, and Islamabad
ABOUT THIS
WORKSHOP:
Digital forces are reshaping almost every
industry, and you already understand the urgency for
transformation. You need to look into options how
Digital Disruption helps you formulate a successful,
innovative strategy for what to do next. Data
Catalog is a fully managed and scalable metadata
management service that empowers organizations to
quickly discover, understand, and manage all of
their data. In a nutshell planning is critical to
the long-term adoption and success of a data catalog
tool. In this course you will be introduced to how
to work through use cases to construct a practical
roadmap of data catalog growth.
OPTIMIZING YOUR DATA
CATALOGUING LEARNING PATH:
Metadata
is foundational to all data work and should be a
top priority of a Data Governance program.
Without an understanding of what data means,
where it comes from, or how it s classified,
it s virtually impossible to extract data s full
value. A data catalog tool provides an
innovative solution for powering Data
Intelligence and Metadata Management with
governance at the core.
But investing in a data catalog is only a first
step. Optimized value can only be fulfilled when
it's embedded into business-as-usual processes
of how users work on a daily basis, creating a
sustainable need and trust in the catalog as
opposed to just knowing it is one of many tools
available. This course is one step forward to
your learning.
COURSE
HIGHLIGHTS:
Technical writing is unique because
of its specialized content. It must convey objectivity
and reach both technical and nontechnical audiences
with exactness and clarity. Along with writing emails,
letters and reports, the technical writer must be able
to prepare definitions, physical descriptions, product
specifications, procedures, test and laboratory
results, and many other kinds of documents.
COURSE
OUTLINE
Unit 1: Information
Infrastructure Challenges and Data
Management
Methodologies
- Understanding
the role of Data Scientist.
- How Does a
Data Scientist Work?
- Describe
Information Infrastructure and Information
Infrastructure Model.
- Information
Infrastructure Model.
- Archive
What is it and its importance.
- Best
practices for storing data sets in an
Archive.
- Information
infrastructure and key challenges.
- Critical
Characteristics of Information.
- Data silo s
are all too Common The Bigger Challenge.
- Understanding
Data Management The Data-driven
Enterprise.
- Types of
Data Management Techniques.
- Common
approaches to the implementation of
archiving solutions.
- Six key
parts of the Data Management Process.
- Mapping
Data to Business Processes using CRUD
Matrix.
- The rise of
the Data Lake A small backdrop.
- Understanding
the difference between ETL, ELT and
Reverse ETL.
- Things you
need to Know about Data Storage
Management.
- Five ways
to optimize data strategy
- Understanding Data
Lifecycle Management.
- Data Management
Challenges and
- Storage Vs Data
Classification.
- Understanding Data
Lifecycle Management DLM.
- Information
Lifecycle Management and an example.
- ILM Three
Storage Strategies.
- Data
Classification.
- Difference between
ILM and DLM.
- Understanding Data
De-Duplication.
- Importance of
Virtual Tape Library.
- Unit 1 Assessment.
Unit 2: Key
Fundamentals of Data Cataloguing
- Traditional
Data Management Practices & Problems.
- Data
Cataloguing as a way forward to
Traditional Problems.
- The Data
Landscape is getting highly complex with
Data flowing across a Multitude of
Changing Systems.
- Solution
that should provide deep insight into the
Data Landscape.
- What is
Data Catalog A Reference Application for
Data Management.
- Data
Catalog as a Way-forward to Traditional
Problems.
- Essential
Data Catalog Capabilities.
- The Six key
components of a Data Cataloguing.
- Business
Value of Data Cataloguing.
- Benefits of
Central Point of Discovery and Data
Transparency.
- Data
Cataloguing Tools Purpose and
Functionality.
- Data
Integration Tools Purpose and
Functionality.
- Data
Catalog Best Practices.
- What
Features to look when procuring a Data
Cataloguing tool.
- Describing
different types of Metadata
Classifications.
- Difference
between Data Cataloguing
and Data Integration tools.
- What
Features to look when procuring a Data
Cataloguing tool.
- High-level
Architecture for Data Cataloguing Tool.
- Customer
Profiles for Data Cataloguing.
- Data
Catalog Use Cases.
- Unit 2
Assessment.
 |
Unit 3: Data
Cataloguing Implementation Strategy
- Understand
the
importance of Data Analysis and Data
Management.
- Data
Catalog
Adoption Strategy Twelve Key Steps.
- Build
a
Metadata Management Strategy and Plan.
- Develop
a
Data Catalog Implementation Strategy.
- Key
Capabilities
Required from a Data Catalog
An Essential Part of your Strategy.
- What to include in
Metadata Management Strategy?
- Metadata
Management Plan Key Requirements.
- Data
Cataloguing
Implementation Strategy and Industry
Solutions.
- Defining
objectives and scope,
and Stakeholder engagement.
- Policies
and procedures.,
Roles and
responsibilities.
- Integration
with Existing Systems.
- Implementing
your
Data Catalog Three types of
approaches.
- How
do you Implement a Data Catalog A
Phased-wise Approach.
- How to Set Up a Data Catalog
for Data Discovery?
- Data
Catalog Challenges and a Step-by-step
Action Plan.
- Critical steps to
secure PII against loss or compromise.
- Understand
Data
Classification.
- Action
plan to mitigate challenges and achieve
business outcomes.
- How to
choose the data catalog tool to
eradicate business challenges.
- Data
Catalog Features that should be
supported by the tool.
- Interoperability
and usability for the Data Lakehouse.
- Unit 3 Assessment.
Unit 4: Data Catalog
and Data Governance Framework Fundamentals
- The
importance for building a Data
Governance Strategy.
- Why
do Organizations need a Data Governance
Framework?
- Importance
of Data Governance and its Key
Principles.
- Data
Governance A core component of Data
Management. strategy.
- Why
Data Governance Matters Issues and
Challenges.
- Who are responsible
for Data Governance? Roles and
Responsibilities.
- Eight
Key Components of Data Governance.
- Regulatory
Compliance
and Data Governance Frameworks
Relationship.
- How Data Governance
frameworks work.
- Some of the Popular Data Governance
Frameworks.
- Why
Data
Governance Matters Issues and
Challenges.
- The DAMA International
Data Management Body of Knowledge.
- Core
knowledge areas of DAMA-DMBOK.
- The DAMA
International Data Management Body of
Knowledge.
- Adopting
the DAMA framework practically to
improve data management.
- Teams
responsible
for implementing Data Governance.
- Best practices for
creating a data governance framework.
- Building a Data
Governance Plan Key Requirements.
- Top Data Governance
Tools.
- Popular data
governance certifications in 2024.
- Unit
4
Assessment.
|
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List of IBM AIX Operating System
List
of
IBM AIX Operating System
