Data Analytics Process and Best Practice II
About This Course
An organisation’s analytics potential depends on its capability to process and manage the acquired data (both internal & external). The credibility and usefulness of sophisticated data analytics solutions rest upon good quality data. But good, clean data cannot always be readily available.
In the era of big data, analytics and advanced technology, sophisticated models can be built and deployed quickly. This course brings the focus back to the fundamentals of exploring, cleaning, preparing the data and the process of data acquisition and management. These processes ensure that the advanced analytics models are built on a strong foundation of data analytics process.
This course has been designed to equip analytics professionals and managers with an understanding of Data Analytics Process and Best Practices II so that their analytics activity downstream will be more credible and useful. This course is part of the Data Science , Graduate Certificate in Business Analytics Practice Series offered by NUS-ISS.
What You'll Learn
This module introduces methods for identifying appropriate business goals for data analytics and determining suitable data analytics approaches and goals
2) Data Processing Fundamentals
This module develops a working knowledge of different ways to collect & explore data.
3) Data Processing Fundamentals Workshop
Hands on workshop in the following topics
Data Collection
Data Audit & Data Quality checks
4) Data Transformation
This module shows the various methods of how to clean the data and prepare them for subsequent analysis.
5) Decision Engineering
This module examines how the results of data analytics can best be implemented to maximise business value for large enterprises
6) Data Transformation Workshop
Hands on workshop in the following topics
Data Visualization led data transformation
Data Transformation Techniques
Feature Engineering
7) Data warehousing basics
This module examines the key building blocks and com5ponents that make up a data warehouse to transform data into information and business insights.
8) Data pipeline basics
This module examines the key building blocks and processes to ensure a resilient and robust data pipeline to feed the data warehouse.
Entry Requirements
Please see course weblink for more information