Creating Trusted, Compliant Data for the Data Driven Enterprise
Having understood the requirements, you will learn what should be in a governance programme. This includes a data governance framework that covers what you need to govern data including roles and responsibilities, processes, policies and technologies. It also includes a master data management strategy and what you need to do to bring your master data under control. We will look at how to manage leverage make use of a business glossary, data modelling, a data catalogue with automated data discovery, data profiling, sensitive data classification and policy enforcement. We look at data cleaning and data integration, to provision master data and reference Data- as-a-Service (DaaS). We also look at how Customer Master Data is being combined with Data Warehouses and Big Data to create new Customer Data Platforms (CDP)
During the seminar we take an in-depth look at the technologies needed in each of these areas as well as best practice methodologies and processes for data governance and master data management.
Many businesses today are operating in a distributed computing environment with data and processes running across the data centre, multiple clouds and the edge. It this environment, with so much going on, data is harder to find and govern. Also master data, the most widely used data in any business, is becoming harder to find, manage and keep synchronised across systems. This two-day in-depth seminar looks at this problem shows how to successfully implement a data governance program including data quality, data access security, data privacy, data retention and master data management to create a 360 degree view of customers, products, suppliers and other core entities. It is intended for chief data officers, enterprise architects, data architects, MDM professionals, business professionals, database administrators, data engineers, and compliance managers responsible for data governance and management of specific master data.
The seminar takes a detailed look at the business problems caused by poorly governed data and how inconsistent identifiers and data names, poor data quality, lack of master data integration and synchronisation can seriously impact business operations, cause unplanned operational costs and destroy confidence in trust of BI and analytics. It also defines the requirements that need to be met for a company to confidently define, manage and govern data as well as create and share consistent reference and master data across operational applications and analytical systems on-premises and in the cloud.
This seminar is intended for business and IT professionals responsible for enterprise data governance including metadata management, data integration, data quality, data protection, master data management and enterprise content management. It assumes that you understand basic data management principles and a high level of understanding of the concepts of data privacy, metadata, data warehousing, data modelling, data cleansing, etc.
Attendees will learn how to set up an enterprise data governance program and to determine what technologies they need for enterprise data governance and master data management (MDM). In addition, they will learn how use key technologies like data catalogues, data classifiers and data fabric to discover and identify data and build an MDM system.
MODULE 1: WHY IS GOVERNANCE OF CORE DATA SO IMPORTANT?
This session looks at the increasingly complex distributed data landscape, the problems it brings and why companies need to invest in provisioning trusted, commonly understood, high quality data services across the enterprise to guarantee consistency. It also looks at why data governance, data integration and data management should now be a core competency for any organisation.
MODULE 2: A METHODOLOGY & TECHNOLOGIES TO GET DATA UNDER CONTROL
Having understood why we trusted data is so critical, this session looks at data governance framework and methodology for getting you core data under control. It also looks at the technologies needed to help govern your data to bring it under control. It also looks at how data catalog software, trainable classifiers, data loss prevention and data fabric software provide the foundation in a modern data architecture to govern data and produce trusted business ready master data for use across the enterprise
MODULE 3: DATA STANDARDISATION & THE BUSINESS GLOSSARY
This session looks at the first step in getting data under control – the need for data standardisation. The key to making this happen is to create common data names and definitions for your data to establish a common business vocabulary in the business glossary of a data catalog.
• Data standardisation using a shared business vocabulary
MODULE 4: AUTO DATA DISCOVERY, DATA QUALITY PROFILING, CLEANSING & INTEGRATION
Having defined your data, this session looks at the next steps in a methodology, to get data under control is discovering where your data is and how to get it under control
MODULE 5: MASTER DATA MANAGEMENT DESIGN AND IMPLEMENTATION
This session looks at the components of a master data management (MDM) and RDM system and the styles of implementation.
MODULE 6: TRANSITIONING TO ENTERPRISE MDM – THE CHANGE MANAGEMENT PROCESS
This session looks at the most difficult job of all – the change management process needed to get to enterprise master data management. It looks at the difficulties involved, what really needs to happen and the process of making it happen.
MODULE 7: FROM MDM TO CUSTOMER DATA PLATFORMS
This last session looks at the emergence of Customer Data Platforms (CDP) that combine Customer MDM, Big Data and Data Warehouses to create a Customer Data
Platform to support Marketing, Sales and Customer Service in the digital enterprise.
If you can not participate this course, you can send someone else instead of you. If cancellation is done less than 14 days before the course start, we will charge 50% of the price. In case of no show without any cancellation, we will charge the whole price. Cancellation fee will also be charged in case of illness.