This course presents a gentle introduction into the concepts of data analysis, the role of a Data Analyst, and the tools that are used to perform daily functions. You will gain an understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering or data mining. You will then learn the soft skills that are required to effectively communicate your data to stakeholders, and how mastering these skills can give you the option to become a data driven decision maker.
제공자:


이 강좌에 대하여
학습자 경력 결과
13%
배울 내용
Explain what Data Analytics is and the key steps in the Data Analytics process.
Differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst.
Describe the different types of data structures, file formats, sources of data, and data repositories.
Identify key elements in the Data Analytics process by analyzing a business case study and its data set.
귀하가 습득할 기술
- Data Science
- Spreadsheet
- Data Analysis
- Microsoft Excel
학습자 경력 결과
13%
제공자:

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.
강의 계획표 - 이 강좌에서 배울 내용
What is Data Analytics
In this module, you will learn about the different types of data analysis and the key steps in a data analysis process. You will gain an understanding of the different components of a modern data ecosystem, and the role Data Engineers, Data Analysts, Data Scientists, Business Analysts, and Business Intelligence Analysts play in this ecosystem. You will also learn about the role, responsibilities, and skillsets required to be a Data Analyst, and what a typical day in the life of a Data Analyst looks like.
The Data Ecosystem
In this module, you will learn about the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks. You will gain an understanding of various types of data repositories such as Databases, Data Warehouses, Data Marts, Data Lakes, and Data Pipelines. In addition, you will learn about the Extract, Transform, and Load (ETL) Process, which is used to extract, transform, and load data into data repositories. You will gain a basic understanding of Big Data and Big Data processing tools such as Hadoop, Hadoop Distributed File System (HDFS), Hive, and Spark.
Gathering and Wrangling Data
In this module, you will learn about the process and steps involved in identifying, gathering, and importing data from disparate sources. You will learn about the tasks involved in wrangling and cleaning data in order to make it ready for analysis. In addition, you will gain an understanding of the different tools that can be used for gathering, importing, wrangling, and cleaning data, along with some of their characteristics, strengths, limitations, and applications.
Mining & Visualizing Data and Communicating Results
In this module, you will learn about the role of Statistical Analysis in mining and visualizing data. You will learn about the various statistical and analytical tools and techniques you can use in order to gain a deeper understanding of your data. These tools help you to understand the patterns, trends, and correlations that exist in data. In addition, you will learn about the various types of data visualizations that can help you communicate and tell a compelling story with your data. You will also gain an understanding of the different tools that can be used for mining and visualizing data, along with some of their characteristics, strengths, limitations, and applications.
검토
- 5 stars80.14%
- 4 stars16.81%
- 3 stars2.09%
- 2 stars0.31%
- 1 star0.62%
INTRODUCTION TO DATA ANALYTICS의 최상위 리뷰
Great course to get the overall idea about what analytics is, where will it be used, various tools. Best part of this course is it has real life data analysts sharing their view points.
Course is really helped me understand the concept of Data Analytics. The viewer's points explained What, Why, and how Data Analytics. And the final assignment gives an exact idea about Data analysis.
I found it very helpful and the lectures gave basic over-view of the data analytics and related fields. I strongly suggest for a beginner to learn this course and make maximum use of it.
Pretty good course. In my opinion the reading material was a bit brief and did not really cover the quiz questions. Other than that though it was pretty clear and relatively easy to understand.
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