The Awesome Microsoft Excel Membangun Karir Impian sebagai Data Scientist.pptx

The Awesome Microsoft Excel Membangun Karir Impian sebagai Data Scientist.pptx

1. The Awesome Microsoft Excel : Membangun Karir Impian sebagai Data Scientist Presented by Moch. Aril Indra Permana

2. Hey I’m, Moch. Aril Indra Permana I am a, CURRENTLY | AM Audit Data Analyst at PT. Bukalapak 2020 - 2021 | Data Scientist at PT. Telkom Indonesia 2018 - 2019 | Data Scientist at PT. Indonesia Indicator

3. Table of Contents Who are Data Scientist? Data Science Skills Data Science Process 01 Overview of Data Science Excel as Data Manipulation Excel as Data Visualization Excel as Statistics Tools 02 Excel as a Data Science Tool Practical Application of Excel with a Real-World Case Study of RFM Analysis: A Hands-On Approach 03 Real Case – Hands on

4. “Data scientists are a new breed of analytical data expert who have the technical skills to solve complex problems and the curiosity to explore what problems need to be solved.” – SAS Institude Who is Data Scientist?

5. Computer Science/IT Math and Statistics Domains/Business Knowledge AI Traditional Research Software Development Machine Learning Deep Learning Data Mining & Engineering Database & Processing Data Management & Visualizations Presentations & Communications Data Science   is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from structured , and  unstructured data and applying the knowledge and insights from that data to solve problems in a wide range of application domains Required Skills and Knowledge

6. 5 REASONS TO BECOME A DATA SCIENTIST

7. Source: https://www.payscale.com/research/ID/Job=Data_Scientist/Salary Source: https://businessoverbroadway.com/

8. DATA SCIENCE PROCESS

9. Role Interaction and Combination 01 Problem Definition

10. “ Data is typically split into two categories: structured and unstructured .” 02 Data Collections

11. 03 EDA & Prep

12. Excel adalah program spreadsheet yang digunakan untuk mengorganisasi , menganalisis , dan mempresentasikan data. 03 EDA & Prep

13. Feature Excel Google Sheets Cost Paid software with different pricing options Free with a Google account Collaboration Limited collaboration features Strong collaboration features, including real-time editing and commenting Data Storage Limited storage space for large datasets Cloud-based storage with no limit on storage capacity Integration Limited integration with other software Strong integration with other Google tools and third-party add-ons Offline Access Available through Microsoft Office suite Limited offline access 03 EDA & Prep

14. Excel for Data Manipulation Data manipulation is the process of changing, transforming, or rearranging data in a particular format to make it more suitable for analysis, interpretation, or processing . It involves various techniques like cleaning, transforming, aggregating, and summarizing data. Data manipulation is a crucial step in the data science process, as it helps to standardize, organize, and prepare data for further analysis .

15. Rearranging data in a specified order based on one or more criteria, such as alphabetical order or numerical value. Displaying a subset of data that meets specific conditions, such as displaying only data that satisfies a certain range of values or criteria A summary table that displays data in a compact format, allowing users to analyze and summarize large amounts of data Combining two or more strings of text into a single string, typically using a specific character, such as a comma or space, to separate the text Removing duplicate values from a dataset, keeping only unique values. Formatting cells based on certain criteria or rules, such as highlighting cells that contain specific values or applying color scales to cells based on their value.

16. Data visualization is the graphical representation of data, information, or knowledge in a visual format. It aims to help people understand and interpret complex data and information by converting it into a visual format such as charts, graphs, maps, and other illustrations. By visualizing data, it is easier to identify patterns, relationships, and insights that might be hidden in raw data. Excel for Data Visualization

17. Excel for Data Analysis RFM  stands for Recency, Frequency , and Monetary value, each corresponding to some key customer trait. These RFM metrics are important indicators of a customer’s behavior because frequency and monetary value affects a  customer’s lifetime value , and recency affects retention, a measure of engagement.

18. HANDS ON

19. Are you interested in becoming a data scientist ?

20. THANK YOU