Data is one of an organization’s most valuable commodities. But how can organizations best use their data? And how does the organization determine which data is the most recent, accurate, and useful for business decision making at the highest level?
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Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
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Niveau débutant
Computer and IT literacy.
Approx. 16Â heures pour terminer
Anglais
Sous-titres : Anglais
Ce que vous allez apprendre
Explore the architecture, features, and benefits of data warehouses, data marts, and data lakes and identify popular data warehouse system vendors.
Design and populate a data warehouse, and model and querydata using CUBE, ROLLUP, and materialized views.
Identify popular data analytics and business intelligence tools and vendors and create data visualizations using IBM Cognos Analytics.
Design and load data into a data warehouse, write aggregation queries, create materialized query tables, and create an analytics dashboard.
Compétences que vous acquerrez
- Data Warehousing
- Cube and Rollup
- Business Intelligence (BI)
- Star and Snowflake Schema
- cognos analytics
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau débutant
Computer and IT literacy.
Approx. 16Â heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Réseau de compétences IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Programme de cours : ce que vous apprendrez dans ce cours
3Â heures pour terminer
Data Warehouses, Data Marts, and Data Lakes
Welcome to your first module! This module provides a gentle but thorough introduction to data warehouse systems, data lakes, and data marts. When you complete this module, you’ll be able to identify and compare data warehouse systems, data mart, and data lake architecture, and understand how organizations can benefit from each of these three data storage entities. Optionally, you’ll explore the workings of IBM Db2 data warehouse system architecture, view use cases, and understand the key capabilities and integrations available with IBM Db2 Warehouse. Then, you’ll learn about three types of data warehouse systems and popular data warehouse system vendors. You will be ready to help your organization assess new data warehouse system offerings when you know the five essential, critical criteria, including total cost of ownership, to evaluate before changing to a new data warehouse system.
3Â heures pour terminer
6 vidéos (Total 33 min), 2 lectures, 3 quiz
5Â heures pour terminer
Designing, Modeling and Implementing Data Warehouses
In this knowledge-packed module, you’ll explore general and reference enterprise data warehousing architecture. You’ll discover how data cubes relate to star schemas. Then you’ll learn how to slice, dice, drill up or down, roll up, and pivot relative to data cubes. Next, you will examine the capabilities of materialized views, their benefits, and how to apply them. You’ll learn how data organization using facts and dimensions and their related tables organizes information. Then, you will explore how to use normalization to create a snowflake schema as an extension of the star schema. You will learn about populating a data warehouse, incremental data updates, verifying data, querying data, interpreting an entity-relationship diagram for a star schema, creating a materialized view, and applying the CUBE and ROLLUP options. ​You’ll also discover how organizations can benefit by implementing staging.
5Â heures pour terminer
8 vidéos (Total 56 min), 3 lectures, 7 quiz
4Â heures pour terminer
Data Warehouse Analytics
In this module, you’ll fast-track your data analytics learning and gain hands-on data analytics experience using IBM Cognos Analytics. After registering with Cognos Analytics, you’ll explore the platform’s capabilities by creating visualizations, building a simple dashboard, and trying out its advanced features.
4Â heures pour terminer
6 vidéos (Total 26 min), 1 lecture, 2 quiz
5Â heures pour terminer
Final Assignment and Final Quiz
In this module, you’ll complete your final course project, which brings together concepts and practices you previously learned in the first three modules. In this final project, you will design and load data into a data warehouse using facts and dimension tables. Then you’ll write aggregation queries using CUBE and ROLLUP functions and create materialized query tables, known as a materialized view. You will complete your project by using IBM Cognos to create an analytics dashboard.
5Â heures pour terminer
3 lectures
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