Introduction to Data Analysis, Finland

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Organizations need to make business decisions more quickly and accurately than ever before. Basing these decisions on data and best practice analysis techniques and less on gut feel or "the way we have always done things" is how today's corporate management is demanding information. A solid foundation of data analysis for business decision making is a critical skill you should have regardless of whether your motive is to obtain or sustain a competitive advantage or simply better steward your resources to serve customers. In this course, you will learn to use data analytics to create actionable recommendations, as well as identify and manage opportunities where data-based decisions can be used to change the way you do business.

This course provides many of the common data analysis tools used to gather, analyze, and adapt your data to feed business decisions. You do not need heavy Excel or data analysis experience. This course includes introductory exercises on Excel add-ins, standard deviation, random sampling, and an introduction to pivot tables and charts. These exercises will show you how to effectively demonstrate basic data analysis functions and reporting in Excel or Google Spreadsheets. We will simplify math jargon and complex symbols and equations to concentrate on what your data can tell you and your organization. In addition, you will learn how to present to those executives, managers and subject matter experts who need to quickly make decisions that drive your organization.

There are no prerequisites for this course.

Anyone involved in operations, project management, business analysis, or management, who needs an introduction to data analysis.

Terms, jargon, and impact of business intelligence and data analytics
Scope and application of data analysis
Impact of analytics on gaining competitive advantage and decision support
Measure the performance of and improvement opportunities for business processes
Need for tracking and identifying the root causes of deviation or failure
Basic principles, properties, and application of probability theory and the normal distribution
Introduction to different methods for summarizing information and presenting results including charts
Statistical inference and drawing conclusions about the population
Sample sizes and confidence intervals, and how they influence the accuracy of your analysis
Forecasting and an introduction to simple linear regression analysis
Interpret your results and draw sound and relevant conclusions on business
Methods and algorithms for forecasting future results and to reduce current and future risk
Process improvement and analysis skills
Where powerful reference material exists and how to leverage to enhance your decision-making

1. Introduction to Data Analysis and Analytics

Definition and history
Current technology environment and the growing availability of data
Role of the business analyst and data analyst
Applications for gaining competitive advantages
Fact-based decision making
Process tracking and control

2. Application of Probability and Probability Distributions

Key concepts and essentials
Decision making under uncertainty
Random variables
Population and samples
The normal distribution
Many business distributions are nowhere near normal. constraints!
Establishing confidence intervals

3. Introduction to Data Mining and Data Warehousing

Data mining concepts and application
Introduction to application benefits of data warehousing

4. Describing Information Needs

Identify operational and executive information classes
Modeling key decisions and the needs for information
Describing key business transactions and documents
Map information needs to underlying data
Executive information needs and the balanced scorecard
Pivot tables in Excel
Tracking and managing business process performance
Selecting measures and targets
Measuring performance and finding performance gaps
Root cause analysis

5. Data Exploration Concepts and Formulas

Basic concepts
Types of variables
Selecting dependent and independent variables
Sample vs. population
Descriptive measures of a sample
Key sample parameters
Variability
Sampling distributions
Sample size
Histograms
Establishing and analyzing correlation among different variables
Explanation of variance

6. Introduction to Risk Management

Uncertainty and risk analysis
Assessing your organization risk culture and level of risk tolerance
Identifying, describing, ranking, prioritizing, and controlling risks
When to use quantitative risk analysis
Important risk management best practices

7. Forecasting

Forecasting methods and models
History of forecasting
Long and short term forecasts
Heuristics
Time series analysis
Establishing trends and business cycles (i.e., seasonality) and confidence limits
Selecting independent variables for predictive models including regression techniques

8. Review

Data analysis and analytics
Probability and distributions
Data mining, data warehousing, and the need for information
Statistic inference, forecasting, and decision support
Next steps options

9. Additional Resources and Exercises

Introduction to Data Analysis 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 Analysis Training in Finland

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Introduction to Data Analysis Training in Finland

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What You Will Learn

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ESSENTIAL TIPS FOR NEW DATA ANALYSTS

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