• Big Data 2018 Workshops

    Workshop A - AI & Data Strategy, Architecture & Governance
    22nd & 23th October 2018
    Hotel Istana Kuala Lumpur

Introduction

Data Strategy is the first step to get the real value out of data. We are strong believers that successful data projects are business-driven and starts with business goals and not just with a Hadoop or Spark cluster. That’s why, we’ll focus our efforts in this workshop to the ways organization can develop a full interoperable data strategy, architecture and use cases while insuring the right data governance in place.

Take away with you skills and strategies on:



How to define a strategy for producing trusted data as-a-service in a distributed environment of multiple
data stores and data sources
How to build a data architecture and business use cases
Measuring the ROI from data
How to organise data in a centralised or distributed data environment to overcome complexity and chaos
Edge Computing Architecture and uses
How data standardisation and business glossaries can help define the data to make sure it is understood
What technologies they need and implementation methodologies to get their data under control


How to apply methodologies to get master and reference data, big data, data warehouse data and
unstructured data under control irrespective of whether it be on-premises or in the cloud


Who should attend?

Data Engineers
Chief Data Officers
Data Architects
Master Data Management Professionals
Big Data Professionals
Data Integration Developers
Business Data Analysts doing self-service data integration
Content Management Professionals
Database Administrators


Compliance Managers who are responsible for data management (including metadata management data
integration, data quality, master data management and enterprise content management)


* This course assumes that you have an understanding of basic data management principles as well as a high level of understanding of the concepts of data migration, data replication, metadata, data warehousing, data modelling, data cleansing, etc.