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Product description
Data for Leaders and Decision Makers E-Learning
Make better business decisions with data – no technical background required.
Data is becoming central to strategic decision-making. This course is designed for managers, team leaders, and executives who want to gain a solid understanding of data and modern data technologies—without needing deep technical skills. It covers data infrastructures, compliance, governance, and how to engage in data projects with confidence.
What you’ll learn:
Overview of modern data sources and infrastructures
Familiarity with tools, frameworks, and platforms at a strategic level
Understanding of data governance and compliance (e.g., GDPR)
Risk management and ethical data usage
How to apply data strategies for better business decisions
Delivered as part of an Agile Learning Kit, the course includes step-by-step tracks, assessments, labs, mentoring, and full access for 365 days.
Why Choose This Training?
Tailored for non-technical leaders and managers
Understand and discuss data without diving into code
Business-focused and practically applicable
Includes e-learning, mentor support, labs, assessments & 365-day access
Agile structure designed for flexible, impactful learning
Who Should Enroll?
This course is ideal for:
Managers and team leaders in any industry
Executives and decision-makers engaging in data projects
Business consultants working with data-driven initiatives
Organizations aiming to foster a data-driven culture
This Learning Kit, with more than 18 hours of online content, is divided into the following tracks:
Demo Data for Leaders and Decision Makers Training
Course content
Track 1: Data Primer
In this track, the focus will be on the fundamentals of data, traditional data architectures, and new age data infrastructures. Courses (2 hours +):
Data Nuts & Bolts: Fundamentals of Data
Course: 30 Minutes
Course Overview
Data, Information, Knowledge, and Wisdom
Sources of Data Generation and Data Formats
Data Terminologies
Data Storage and Backup
Data Migration and ETL
Advantages of Data Integration
Data Visualization and Reporting
Data Engineering Languages
Course Summary
Traditional Data Architectures: Relational Databases
Course: 35 Minutes
Course Overview
Different Types of Databases
Relational Database Design
Normalization and Denormalization
Normal Forms and Their Use Cases
OLTP Information Systems
OLAP Information Systems
Common Use Cases of Data Warehousing
Traditional Data Architectures
How Data Mining and Data Marts Are Used
How to Scale a Database
Course Summary
Traditional Data Architectures: Data Warehousing and ETL Systems
Course: 40 Minutes
Course Overview
Data Warehousing for Business Intelligence
Data Warehouse Architecture
Data Warehousing Schemas
Dimension Table Use Cases
Fact Tables in a Data Warehouse
Keys in Data Warehouse Schemas
What Is ETL?
What Is ETL, ETL Framework, and Process Flow?
Extract, Transform, and Load (ETL) Tools
Extract, Transform, and Load (ETL) Best Practices
Course Summary
New Age Data Infrastructures: Factors Driving Data Infrastructures
Course: 38 Minutes
Course Overview
Traditional Data Architecture
Limitations of Traditional Data Architecture
Limitations of Traditional ETL Systems
Compare ETL and ELT Systems
Demand for Multi-model Data Platforms
Multi-model Databases
Commonly Used Data Sources
Real-time Data Processing
Traditional and New Age Business Intelligence
The Evolution of Analytics
Course Summary
Assessment:
Data Primer
Track 2: Big Data Infrastructures
In this track, the focus will be on big data concepts, non-relational data, and big data analytics. Courses (3 hours +)
Big Data Concepts: Getting to Know Big Data
Course: 43 Minutes
Course Overview
What Is Big Data?
Sources of Big Data
Characteristics of Big Data
Structured and Unstructured Data
Big Data Analytics
Advantages of Big Data Analytics
Big Data Analytics: Domain Use Cases
Big Data Analytics: Netflix Use Case
Big Data Analytics: Amazon Use Case
Major Challenges in Big Data
Course Summary
Big Data Concepts: Big Data Essentials
Course: 46 Minutes
Course Overview
Raw Data and Big Data
Data Warehousing and Big Data
Big Data Computing Systems
Horizontal and Vertical Scaling
Features, Benefits, and Use Cases of Hadoop
Hadoop: Components
Hadoop: Migration to the Cloud
Hadoop and Cloud Computing
Features of Big Data Storage Systems
In-memory Storage Systems
Course Summary
Non-relational Data: Non-relational Databases
Course: 52 Minutes
Course Overview
Non-relational Databases
The NoSQL Approach
Benefits of NoSQL
Document Databases
Key-value Data Stores
Graph Databases
Columnar Databases
HBase Architecture
Multi-model Databases
Next Generation NewSQL Databases
Course Summary
Big Data Analytics: Techniques for Big Data Analytics
Course: 39 Minutes
Course Overview
Big Data Analytics Challenges
Big Data Analytics Stack Layers
Big Data Ingestion
The Data Processing Layer
The Data Storage Layer
Pillars of Big Data Architecture
Batch Processing and Big Data
Stream Processing and Big Data
Lambda Architecture and Use Cases
Kappa Architecture
Course Summary
Big Data Analytics: Spark for High-speed Big Data Analytics
Course: 51 Minutes
Course Overview
The Core Characteristics of Apache Spark
Components of the Apache Spark Architecture
Apache Spark Use Case: Uber Using Spark
Apache Spark Use Case: Alibaba Using Spark
Apache Spark Use Case: The Healthcare Industry
Apache Spark vs. Hadoop
Top Apache Spark Use Cases
Apache Spark's Main Features
Apache Spark Performance Optimization Techniques
Apache Spark Best Practices
Course Summary
Assessment:
Big Data Infrastructures
Track 3: Raw Data to Insights
In this track, the focus will be on data mining and decision making. Courses (3 hours +)
Data Mining and Decision Making: Modern Data Science Lifecycle
Course: 54 Minutes
Course Overview
Data Science vs. Data Analysis
Data Science Project Steps and Processes
Establishing Data Science Project Business Value
Data Preparation Processes
Using Descriptive Analysis to Drive Decision-making
Using Predictive Analytics to Drive Decision-making
Interpreting Predictive Models in a Business Context
Machine Learning: Model Validation
Machine Learning: Model Implementation
Case Study: Data-driven Decision-making
Course Summary
Data Mining and Decision Making: Data Preparation & Predictive Analytics
Course: 41 Minutes
Course Overview
Common Industrial and Commercial Data Sources
Data Collection Skills and Methods
Data Validation Best Practices
Data Cleaning Techniques
Data Exploration: Summary Statistics
Data Exploration: Summary Statistics II
Data Exploration: The Power of Visualization
Data Exploration: Advanced Visualization
Feature Engineering: Feature Generation
Feature Engineering: Feature Reduction
Course Summary
Data Mining and Decision Making: Data Mining for Answering Business Questions
Course: 1 Hour, 3 Minutes
Course Overview
Data Science, Data Analytics, and Machine Learning
Machine Learning Engineer vs. Data Science
Types of Machine Learning
How Do Machine Learning Algorithms Work
Data Mining: Association Rules
Data Mining: Anomaly Detection
Data Mining: Customer Segmentation
Case Study: Walmart and Market Basket Analysis
Case Study: Customer Segmentation Analysis
Importance of Predictive Analysis in Business
Course Summary
Data Mining and Decision Making: Predictive Analytics for Business Strategies
Course: 57 Minutes
Course Overview
Data, Deep Learning, and Artificial Neural Networks
Artificial Neural Networks
Business Problems: Regression
Business Problems: Classification
Business Problems: Time Series
Business Problems: Actionable Recommender Systems
Recurrent and Convolutional Neural Networks
Natural Language Processing (NLP)
Computer Vision
World of Analytics: Integrated Futuristic Vision
Course Summary
Assessment:
Raw Data to Insights
Track 4: Emerging New Age Architectures
In this track, the focus will be on cloud data platforms, data lakes, and modern warehouses. Courses (5 hours +)
Cloud Data Platforms: Cloud Computing
Course: 52 Minutes
Course Overview
Cloud Computing and Its Characteristics
Cloud Computing: Use Cases and Benefits
Cloud Computing Services: Storage and Compute Power
Types of Cloud Compute Power
Types of Cloud Storage
Cloud Computing Models: PaaS, IaaS, SaaS, and FaaS
Cloud Computing Model Comparison
Components of Cloud Computing Architectures
Cloud Service Provider Comparison
Cloud Elasticity and Scalability
Course Summary
Cloud Data Platforms: Cloud-based Applications & Storage
Course: 53 Minutes
Course Overview
Deploying Applications on Cloud Platforms
Characteristics of Cloud-ready Applications
Types of Cloud Deployment Models
Cloud Deployment Tools
Considerations for Cloud Application Deployment
CPU Virtualization, Memory, and I/O Devices
Cloud Storage Platforms
Cloud Storage Technologies
HDFS and Amazon S3
Types of Data Centers
Course Summary
Cloud Data Platforms: AWS, Azure, & GCP Comparison
Course: 56 Minutes
Course Overview
Cloud Data Platforms: Amazon Web Services
Cloud Data Platforms: Microsoft Azure
Cloud Data Platforms: Google Cloud Platform
Cloud Analytics
Popular Cloud Analytics Tools
Cloud Computing Challenges: Security
Cloud Computing Challenges: Compliance
Cloud Computing Challenges: Cost Management
Cloud Computing Challenges: Governance
Future of Cloud Computing
Course Summary
Data Lakes and Modern Data Warehouses: Data Lakes
Course: 1 Hour, 19 Minutes
Course Overview
Data Lake Evolution
Modern Data Lake Architecture
Data Lakes: Key Concepts
Data Lake Maturity Stages
Data Swamps
Data Lake Platforms
Data Lake Platforms
Governed Data Lakes
Data Lakes: Risks and Challenges
Data Lakes vs. Data Warehouses
Course Summary
Data Lakes and Modern Data Warehouses: Modern Data Warehouses
Course: 1 Hour, 10 Minutes
Course Overview
Data Warehouses and Its Characteristics
Modern Data Warehouses: Key Concepts and Stages
Amazon Redshift
Google BigQuery
Modern Data Warehouses: Architecture and Processes
Modern Data Warehouses: Techniques
Data Warehouse Solutions: Batch Processing
Data Warehouse Solutions: Real-time Processing
Data Warehouse Solutions: Streaming Analytics
Hybrid Modern Data Warehouse
Course Summary
Data Lakes and Modern Data Warehouses: Azure Databricks & Data Pipelines
Course: 1 Hour, 2 Minutes
Course Overview
Azure Databricks: Features and Architecture
Azure Databricks: Pros and Cons
Snowflake Data Warehouses: Features and Architecture
Snowflake Data Warehouses: Pros and Cons
Data Pipelines
Components of a Data Pipeline
Advantages of a Data Pipeline
Types of Data Pipeline Tools
Comparing Data Pipeline Tools
Building a Data Pipeline
Course Summary
Assessment: Emerging New Age Architectures
Track 5: Data Governance and Management
In this track, the focus will be on modern data management. Courses (3 hours +)
Modern Data Management: Data Management Systems
Course: 1 Hour, 3 Minutes
Course Overview
Data Management Strategies
Mastering Raw Data
Identifying Domains and Data Sources
Data Integration across Domains
Transactional and Non-transactional Data
Data Management Architectures
Technical Implementation Considerations
Data System Alignment
State of Maturity across Domains
Metadata Management
Course Summary
Modern Data Management: Data Governance
Course: 1 Hour, 6 Minutes
Course Overview
Data Stewardship
Establishing Governance across Domains
Data Compliance - Issues and Strategies
Data Integration Life Cycle
Data Risks and Security
Data Protection, Privacy, and Compliance
Improving Data Quality through Governance
The Entity Resolution Process
CRUD Basic Functions
Building a Data Governance Business Case
Course Summary
Modern Data Management: Data Quality Management
Course: 1 Hour, 8 Minutes
Course Overview
Data Quality Management in a Business Environment
The Data Quality Improvement Cycle
Data Quality Management Activities
The Importance of Reference Data
Improving Data Quality with Data Compliance
Data Performance Measurements
Continuous Improvement of Data Management
Data Management, Governance, and Compliance
Solving Data Governance and Compliance Issues
Next-generation Cloud Data Management Solutions
Course Summary
Assessment:
Data Governance and Management
Practice Lab: Data for Leaders and Decision-makers
In this lab, explore technologies, tools, frameworks, and platforms at a high level for enabling the managers and leaders to comfortably get engaged in data projects. Learners will also explore various data compliance issues, data governance, and various data strategies to be adopted for making better data-driven decisions that are critical for the business. Tasks performed in this lab include: Loading, cleaning, preprocessing and visualization of data using Python Libraries Designing Data Governance Strategy for better data compliance Creating data lake infrastructure for banking company Creating Big Data Architecture for streaming Creating architecture for ecommerce company on Azure cloud Formulating data quality and management steps for manufacturing company Creating predictive model to predict churning of customers Creating time series model for US Stocks with feature engineering
Specifications
Article number
128306674
SKU
128306674
Language
English
Qualifications of the Instructor
Certified
Course Format and Length
Teaching videos with subtitles, interactive elements and assignments and tests
Lesson duration
18 Hours
Assesments
The assessment tests your knowledge and application skills of the topics in the learning pathway. It is available 365 days after activation.
Online Virtuele labs
Receive 12 months of access to virtual labs corresponding to traditional course configuration. Active for 365 days after activation, availability varies by Training
Online mentor
You will have 24/7 access to an online mentor for all your specific technical questions on the study topic. The online mentor is available 365 days after activation, depending on the chosen Learning Kit.
Progress monitoring
Access to Material
365 days
Technical Requirements
Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge.
Support or Assistance
Helpdesk and online knowledge base 24/7
Certification
Certificate of participation in PDF format
Price and costs
Course price at no extra cost
Cancellation policy and money-back guarantee
We assess this on a case-by-case basis
Award Winning E-learning
Tip!
Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform.
Heeft u vragen over dit product of hulp nodig bij het bestellen? Onze AI-chatbot is 24/7 beschikbaar, of neem contact op via [email protected] of bel +31 36 760 1019
Heeft u vragen over dit product of hulp nodig bij het bestellen? Onze AI-chatbot is 24/7 beschikbaar, of neem contact op via [email protected] of bel +31 36 760 1019
Data for Leaders and Decision Makers E-Learning Training Certified Teachers Exam...
€360,58€298,00
Specifications
Article number
128306674
SKU
128306674
Language
English
Qualifications of the Instructor
Certified
Course Format and Length
Teaching videos with subtitles, interactive elements and assignments and tests
Lesson duration
18 Hours
Assesments
The assessment tests your knowledge and application skills of the topics in the learning pathway. It is available 365 days after activation.
Online Virtuele labs
Receive 12 months of access to virtual labs corresponding to traditional course configuration. Active for 365 days after activation, availability varies by Training
Online mentor
You will have 24/7 access to an online mentor for all your specific technical questions on the study topic. The online mentor is available 365 days after activation, depending on the chosen Learning Kit.
Progress monitoring
Access to Material
365 days
Technical Requirements
Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge.
Support or Assistance
Helpdesk and online knowledge base 24/7
Certification
Certificate of participation in PDF format
Price and costs
Course price at no extra cost
Cancellation policy and money-back guarantee
We assess this on a case-by-case basis
Award Winning E-learning
Tip!
Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform.
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