Introduction to Data Preparation for Self-Service Analytics, Finland

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The once simple world of data preparation—ETL for operational data integration—has become increasingly complex. Terms such as data wrangling and data blending indicate some of the challenges. The exciting work of analytics doesn’t work well until the data is ready for meaningful analysis. The scope of big data, the variety of data uses, and the emergence of business-friendly data visualization and analysis tools all contribute to the complexity.

A recently emerged category of technologies helps to meet the challenges with business-friendly tools for data integration and preparation. When your analytics projects spend more time finding and fixing data than analyzing the data, you really need to make a change. Learn about the tools and techniques that can help individuals and teams—both business and technical—to cleanse, combine, format, and sample data for analytics.

There are no prerequisites for this course.

Business managers, business analysts, data analysts, and data scientists who need to accelerate and simplify data preparation activities; BI and analytics developers who face the daily challenges of complex data preparation; technical managers and architects who need to integrate data preparation technologies into the BI and analytics toolkit; everyone who struggles with getting the right data in the right forms for effective analytics.

The common challenges of data preparation in the age of big data
Techniques for data preparation that improve both speed and quality of analytics
The data management and governance benefits of data preparation technologies
The landscape of tools and technologies for modern data preparation
To identify the data that is best suited to your analytic needs
To understand the data and the challenges inherent in that data
To define and specify data cleansing, formatting, and blending needs
To understand and apply principles of iterative and adaptive data preparation

Module 1 – Data Preparation Basics

Data Preparation Defined
Historical Perspective – How Did We Get Here?
The Need for Self-Service Data Preparation
Historical Perspective
Introduction to Data Preparation Tools
- Types of tools
- Programming/scripting vs. visual interface
- Standalone vs. integrated into analytics platforms
- Cloud, on-premises, and hybrid deployment
- Machine learning and data preparation
Users of Data Preparation Tools
- Data scientists
- Data engineers
- Business analysts
- Data analysts
- oInformation workers
Data Preparation in Analytics Architecture
Data Preparation and Analytics Life Cycle
- Continuous exploration and discovery
- Iterative and adaptive

Module 2 – Data Discovery

Data Sources
- Enterprise databases
- Local data
- Desktop data
- Cloud data
- Web data
- Files
- NoSQL
- Geospatial
- Media
Data Sourcing
- Choosing data sources
- Physical data source connections
- Virtual data source connections
Data Exploration
- Understanding content
- Estimating quality
- Discovering patterns
- Discovering data types
- Discovering data structure
- Discovering data relationships
- Data enrichment opportunities
- Developing data profiles
- Capturing metadata

Exercise 1 – Data Exploration and Data Sourcing

Module 3 – Data Transformation

The Scope of Data Preparation
Improving Data
- Standardization and conforming
- Cleansing and quality
- De-duplication
Enriching Data
- Derivation
- Appending
- Aggregation
Formatting Data
- Aggregation
- Sorting and sequencing
- Pivoting / de-pivoting
- Sampling and filtering
- Masking sensitive data
- Constructing records
Data Blending
- Blending defined
- Blend vs. join
- Blending vs. Warehousing

Exercise 2 – Data Transformation and Data Blending

Module 4 – Data Governance

Data Validation
- Visual validation
- Rules-based validation
- Data auditing
Data Protection
- Activity logging
- Activity audits
Data Management
- Metadata management
- Data lineage
- Model on use – “just in time” data models
- Data curation – what and why

Module 5 – The Technology Landscape

Data Preparation Platforms
- Core functions and features
Product Overviews and Selected Demonstrations

Introduction to Data Preparation for Self-Service Analytics Training Course in Finland

Finland is a country located in northern Europe. Helsinki is the capital and largest city of the country. The majority of the people are Finns but there is also a small Lapp population in Lapland, where the country is famous for the Northern Lights. Finland's national languages are Finnish and Swedish.

Known for its vast forests, lakes, and natural beauty, Finland is one of the world's largest producers of forest products, such as paper, pulp, and lumber. One of the world's largest sea fortresses Suomenlinna, Rovaniemi with the "White Nights", dogsled safaris and of course the Northern Lights are what makes Finland so popular for tourists. Finland is one of the best places in the world to see the Northern Lights and attracts millions of tourists during its seasons.

Finland is home to a thriving technology industry and is widely recognized as one of the world's leading technology hubs. Companies such as Nokia and Rovio (creator of the popular game Angry Birds) are based in Finland. Some of the key factors that have contributed to Finland's success in technology include; strong investment in research and development, a highly educated workforce and fundings.

Finland has a strong educational system, and is widely regarded as one of the world's most literate countries. In fact, Finland's literacy rate is one of the highest in the world, and its students consistently perform well in international tests of math and reading ability.

Also, as a pioneer in environmental sustainability, Finland is known for its efforts to reduce its carbon footprint and promote clean energy. This Nordic country is also famous for its unique and distinctive cultural heritage, including its traditional folk music and its elaborate traditional costumes.

Helsinki, Finland's capital city, is the country's business center. Helsinki is Finland's largest city, and it is home to many of the country's major corporations and organizations, including many of the country's leading technology firms. The city is also a commercial, trade, and financial center, as well as one of the busiest ports in the Nordic region.

Take advantage of our diverse IT course offerings, spanning programming, software development, business skills, data science, cybersecurity, cloud computing and virtualization. Our knowledgeable instructors will provide you with practical training and industry insights, delivered directly to your chosen venue in Finland.

Introduction to Data Preparation for Self-Service Analytics Training in Finland

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Introduction to Data Preparation for Self-Service Analytics Training in Finland

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