Data Warehousing Fundamentals

COURSE FEATURES

Duration

3 Days

Skill level

All levels

Course tailored to participants' expertise.

Language

RO / EN

Type

In-class / Online-live

Assessments

Yes

Custom Training

Open Class

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The Data Warehousing course covers concepts and definitions, as well as concrete examples that clearly illustrate the following terms: from data modeling and processing to performance, optimization techniques and tuning, security, and hardware.

This course is taught in Romanian, with course materials available in either English, or Romanian. The course can be customized - on request.

DAY

TOPICS

CONCEPTS, DEFINITIONS

What is and what is the purpose of a DW? Brief history, evolution and future

DW as a BI component. Generalities. Peculiarities. Characteristics

Definitions. The approach of Inmon vs. Kimball. Advantages and disadvantages of these approaches

Operational vs. analytical: OLTP vs. OLAP. Relational/Multidimensional/Hibrid OLAP

Stages from the business requirement to reporting the results

DW DESIGN. DATA LOGICAL MODELING

Relational modeling

Entity. Attribute. Cardinality. Integrity

Normalization: 1NF, 2NF, 3NF

Dimensional modeling

Dimensions. Facts

Dimensions and advanced facts. Time dimension. Events. Hierarchy. SCD

Denormalisation.

Schemes (STAR, SNOWFLAKE, FACT CONSTELLATION)

Processes, flows

DW DESIGN. PHYSICAL DATA MODELING

Migrating from the logical to the physical model

Data structures

Tablespaces

Table, indexes, materialized views

Natural keys, surrogate keys

Constraints

DAY

TOPICS

DW ARCHITECTURE

Definitions and concepts: DIF, SOR, BI.

Relational vs. analytical. Data Warehouse vs. Data Mart

Data Integration Framework (DIF)

Modeling Data Integration

Data Integration Development

Data integration architectures

Stages of data integration processes

Requirements for data integration (business, data sourcing system)

Data integration design

Creating the data integration model (conceptual, logical and physical)

Standards for data integration

Reusable components

Uploading historical data

The prototype for data integration

DI testing

Processes for DI

Data integration services: extract, transport, data business & transformation, load

Other services: data quality, process management, audit, Operation Management

DAY

TOPICS

EXTRACTING, TRANSFORMING AND LOADING DATA INTO DW

ETL vs. ELT

Source operating systems. Heterogeneous data sources

Data quality. Data preparation and access. Key generation

Data extraction and transport from source systems

Data transformation

Processing of dimension tables

Processing fact tables

Data uploading

Data Aggregation

Processes and dependencies between processes

Error logging and handling

Administration. Planning. Monitoring. Support

Data using for BI

Productivity. Specialized tools

Applicaţions (Oracle): Data Integrator, Warehouse Builder, Workflow Builder

OLAP

The multidimensional model. MOLAP, ROLAP, HOLAP

The benefits of cubes (query performance, incremental update speed; improving the analytical content of BI applications)

Design and management of data cubes (Analytical Workspace Manager)

Querying cubes using SQL (cubes organized as materialized views, query rewrite; cube-views)

Contact Us

Feel free to leave us your thoughts so we can discover the solution together!

academy@esolutions.ro

Get in touch

0753.029.187

Our address

Budisteanu Office Building, Strada General Constantin Budisteanu Nr. 28C, Sector 1, Bucuresti

academy@esolutions.ro

Get in touch

0753.029.187

Our address

Budisteanu Office Building, Strada General Constantin Budisteanu Nr. 28C, Sector 1, Bucuresti

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