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Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 9:40pm On Jul 08, 2021 |
Introduction This thread is intended to provide a comprehensive guide and proper direction for anyone aspiring to pursue a career in the data analytics field. it will help you to understand where you are, how to start and where to start from. Most of the things will be based on my personal research, teaching and work experience among others. I will make time to be updating it until we are done. Where to start I will suggest you start from Course 1 : Let me call it Understanding the Data Ecosystem You should cover the following in this course 1 Definition of data related terms 2 Data sources and data format 3 Tools used in data ecosystem 4 Frameworks available in the data ecosystem 5 Assessment of where you are in relation to where you want to go 6 The most important skill sets you must have 7 Various domains and how they use data 8 Data related job Titles and their requirements 9 And many more like Business metrics, KPI etc This is a purely theoretical class and will prepare your mind on what is ahead of you Recommended Study Materials 1 https://www.coursera.org/learn/foundations-data?specialization=google-data-analytics 2 https://www.coursera.org/learn/introduction-to-data-analytics?specialization=ibm-data-analyst 3 Any other course that looks like any of the above listed courses will be a good starting point, It will help both technical and non technical people Duration of Study 1 to 3 weeks depending on your speed Key takeaways 1 Broad understanding of what you are going into 2 The relevance of your existing degrees and your domain knowledge as it relates to data 3 Early Decision on domain of interest 4 The exact requirement for your desired job title 5 And many more ...... To be Continued....... 9 Likes 4 Shares |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by Immarocks(f): 9:15am On Jul 09, 2021 |
Hello...I am interested in this can you continue please 1 Like |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 9:46am On Jul 12, 2021 |
Part 2 Course 2: Spreadsheet Application 1 Microsoft Excel 2 Google Sheet The above are the most popular spreadsheet applications out there in the market. They are very similar and the knowledge of one can help you learn the other very easily. If you plan to restrict your work to Nigeria and Nigerians, You don't need to learn Google sheet. Details of the course 1 You will learn data entry and validation, sorting, filtering, conditional formatting among other things 2 You will see data in a very big flat table for the first time 3 You will learn functions for different categories, industries and domains and how they are used. 4 You will learn different techniques for data cleaning and preparation 5 You will learn how to prepare reports, charts, dashboards and many more 6 Excel is very wide and deep and can be enhanced further by the use of plugins 7 You will learn syntax for writing functions and codes with autocomplete on your side 8 You will learn how to nest functions, different lookups and their use cases 9 You will learn how to summarize data with pivot tables 10 Excel VBA is a course on it's own inside Excel 11 Statistical Analysis is a course on it's own inside Excel with it's own plugin and many more 12 The major limitation of Excel is that it can only accept 1,048,576 rows by 16,384 columns by default 13 Microsoft has broken that limitation by introducing Power Query and Power Pivot in Excel 5 Likes 2 Shares |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 9:53am On Jul 12, 2021 |
Recommended materials for learning spreadsheet Any Good learning material for Excel must meet the following conditions 1 Create a business problem or scenario 2 Provide a dataset for the business problem 3 Guide you to solve that particular business problem Can I get a Job with only Excel? The answer is YES but you will need to be a master in Excel. The available job titles are Excel Expert adviser, Excel Trainer, Data entry operator, Data Validation operator, Data Correction and checking operator among others. You can enhance your current role with advanced Excel skills. Key Takeaways You must pay close attention to whatever thing you are doing in Excel and observe their outcomes carefully because you are going to do the same thing in SQL, Python, R etc 3 Likes 1 Share |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by Rictech: 2:42pm On Jul 12, 2021 |
Lovelybobo, you are doing well. Please continue |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 10:11am On Jul 14, 2021 |
part 3 SQL and Databases SQL is the language you use to communicate with databases and since most of the datasets you will be working with will either be file format which Excel can handle or reside in a database in which SQL is needed. what to learn SQL for Microsoft SQL Server SQL for Any open source database server SQL for any Big Data database The SQL required for each database is slightly different but the concept is the same. Note The are four categories of programming skills available Basic Intermediate Advanced Expert About 80% of the learning materials you will come across will provide you with the Basic knowledge you will need, while 10 to 15% others will give you some intermediate skills. what you learn in Basics SELECT, FROM, WHERE, GROUP BY, HAVING, ORDER BY, LIMIT and a lot of AGGREGATE FUNCTIONS. How to progress Once you have mastered the basics, you can join forum for SQL and Databases or register in an online practice site where you can begin to attempt real business questions and see different business scenarios and then continue with your learning by solving those problems. Personal Portfolio You must begin now to build personal portfolio to showcase your progress Key takeaways Repeat the task you did in Excel using SQL and see which one is easier SQL is the second most important skill you will need and must have after COMMUNICATION ....To be Continued.... 7 Likes 1 Share |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 10:27am On Jul 16, 2021 |
Part 4 Course 4 - Statistics, Business Intelligence and Visualization Optional or prerequisite 1 Introduction to Statistics 2 Descriptive Statistical Analysis The above is an optional course depending on your background and previous studies Main Course Power BI Tableau QlikView Looker Cognos 4 Categories of Data Analytics 1 Descriptive analysis - What happened in the past 2 Diagnostics analysis - Why did it happen 3 Predictive analysis - What is likely to happen in the future 4 Prescriptive analysis - Recommend actions we can take to affect the future outcome Level of Statistics you will need now You must understand descriptive statistics very well to be able to relate very effectively with your dataset. Things you must cover in your basic statistics knowledge are measure of central tendency like mean, mode, median, Average, Variance, Range, Standard Deviation, Discrete and continuous variable, Qualitative and Quantitative variable, correlation etc BI and Visualization Details Microsoft Power Bi is the most popular, followed by Tableau and QlikView. Looker from Google and Cognos from IBM are in the emerging market based on Gartner 2021 report. You decide what you want to learn and why Power Bi can be subdivided into 3 - Visualization and Dashboard, M Language and DAX, It is powerful and can connect to different data sources. Tableau is believed to be an intelligent BI and visualization tool with its grouping of variables into measures and dimensions. It has support for auto suggestion of charts and enforcing industry best practices. QlikView is good and worth looking at. What you will study Measures, Calculated columns, data cleaning, data preparation, different visualizations and their use cases, merging datasets, building models etc. Major Job Titles Business Analyst BI Analyst Key Takeaways You must understand all the 19 most common KPI for business You must understand the most basic charts and their use cases. ....To be Continued....... 3 Likes 1 Share |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by Deasegun19(m): 5:11pm On Jul 17, 2021 |
Thank you for this. 1 Like |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 9:34pm On Jul 17, 2021 |
Part 5 Course 5 - Computational thinking and Programming Prerequisite or Optional 1 Computational Thinking 2 Problem Solving with Computer The above two courses will bridge the gap for Non Technical, and other people who wants to go into programming. It will lay a solid foundation for you and open you up to begin to think problem solving and computationally. Recommended Study material CS50 from Harvard University and many others in that category Main Course 1 Python 2 R Major Difference between Python and R R was developed by statisticians to help them in their statistical analysis and till date R is most suited statistical analysis. Python was developed as an automation tool kit to help the developer and over time many people have contributed a lot of Library, packages and modules to make python great. Python is great for Data Science, Machine Learning, AI and Automation. Details of What you will learn in Python Python basics, Numpy, Scipy, Pandas, Matplotlib, seaborne etc Personal project and Portfolio You must build personal portfolio by solving problem with different datasets to showcase your skills. my personal recommendations are 2 projects on Excel 2 projects on SQL 2 projects on Power Bi and/or Tableau 2 projects on Python Note: the more projects you have the better for your career Major Job Titles Data Analyst, Business data analyst, Finance data Analyst among others Major certifications to consider Google Data Analytics Professional Certificate IBM DATA ANALYST PROFESSIONAL CERTIFICATE Non technical Skills to have 1 Communication 2 Presentation 3 Curiosity 4 Business acumen 5 creative and critical thinking etc ...To be Continued..... 2 Likes |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by DeevaB: 3:54pm On Jul 18, 2021 |
I am keenly interested in this with a good knowledge of excel. Willing to learn more, please continue and how we get started. Thank you. 1 Like |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by munstaqq: 6:45pm On Jul 18, 2021 |
Between Power BI and Tableau, which is advisable to learn? God bless you for starting this thread. I'm grateful. |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by muhamadnur: 7:12pm On Jul 18, 2021 |
Thanks for opening this nice thread Ready to learn and following |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 10:30pm On Jul 18, 2021 |
munstaqq: Power Bi and Tableau are very good. This is my personal recommendation, If you can, please learn the two. Once you get a job you focus on the one the company is using. Learning the two will double your opportunities Finally, You can conduct your personal research and decide on what to learn |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 11:49pm On Jul 18, 2021 |
Part 6 Course 6 : The application of our Data analyst knowledge to a task The Role, Task and activities of a Data Analyst using Nairaland personal account as case study 1 Client Question I need the summary and detailed account analysis of lovelybobo on Nairaland Data Analyst Approach to the problem Let us assume we have the correct and right dataset in our hands to respond to the client Data analyst personal Questions that will lead to insight Question 1 - How long has lovelybobo spent on Nairaland Question 2 - When did lovelybobo register on Nairaland Question3 - The time he has spent, can it be arranged in hours, days, weeks, months, quarter etc Question 4 - What section does he spend his time Question 5 - What is the average time spent on each section Question 6 - How many topics did he create Question 7 - How many thread did he comment on Question 8 - Which of his thread is the most popular Question 9 - What is the total number of days he will spend at the end of 2022 Question 10 - Has be been banned before and for how long The questions can go on and on Answers to the Questions and the insight they provide Answer 1 - This question will require you to aggregate a column using SUM FUNCTION and the answer will be place on the Summary page of the DASHBOARD. It is a main feature of the result Answer 2 - This should be easily located on the Date column of your dataset since you must register to post a thread, this will also be on the DASHBOARD because it is major indicator Answer 3 - This task requires you to perform a calculation that involves conversion, minutes to hours, hours to days, days to weeks depending on what you want your final output to be. Answer 4 - this will require a BAR CHART OR PIE CHART and AGGREGATION OF Time GROUP BY Sections Answer 5 - AVERAGE AGGREGATE will be performed on each section Answer 6 - COUNT FUNCTION will be used and parameter to identify created topics figured out Answer 7 - COUNT FUNCTION will be used and parameter to identify comments figured out Answer 8 - SORTING OPERATION will be performed on the list of his thread Answer 9 - Predictive analysis Answer 10 - DOMAIN KNOWLEDGE about Nairaland will be needed to answer this question. Note Some times your task may require you to scrap a web page Python Libraries for web scrapping are Request BeautifulSoup Selenium Scrapy and many others ......To Be Continued........ 7 Likes |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by munstaqq: 7:22am On Jul 19, 2021 |
lovelybobo:Oh okay. Thank you. Please don't give up on this thread. We are following keenly. 1 Like |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by dfo12(m): 7:24am On Jul 19, 2021 |
Thank you for this tread. I am a Chemical Engineer with no background knowledge of programming. I started learning Python on my own using some videos and printed text. I really want to learn programming to become a data scientist. Do I continue with the Python programming, or there's something fundamental I need to learn first before moving? 1 Like |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 8:39am On Jul 19, 2021 |
Part 7 The Final part for data analyst The Summary summary of Data Analyst journey What to learn 1 The Data ecosystem 2 Spreadsheet Applications 3 SQL and Databases 4 Descriptive Statistics, BI and Visualization 5 Computational Thinking, Problem solving with computer and Programming Language 6 Personal Portfolio is a must What you should be able to do 1 Ability to solve data related problems 2 Extract, Transform and Load data 3 Descriptive analysis 4 Diagnostic analysis When to seek for help or give up After you have studied all the content and you are given a dataset and you don't know what to do or how to start, please just humble yourself and seek for help. If the help did not work, then, the journey is not for you. My final word to the Data Analyst It is an interesting career path with plenty reward but there are challenges on the way. You must become a friend to constant study. THIS IS THE END FOR THE DATA ANALYST THE BEGINNING OF DATA SCIENCE JOURNEY ..... To be Continued........... 7 Likes |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 8:43am On Jul 19, 2021 |
dfo12: Please follow the instructions on this thread. Python is not the first course to start with. 2 Likes |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by munstaqq: 10:07am On Jul 19, 2021 |
dfo12: I think starting with Python will make you give up on data science real soon. Start from the basics like Excel, SQL, Tableau or Power BI and then Python or R, in that order. 5 Likes |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by dfo12(m): 7:18pm On Jul 20, 2021 |
munstaqq: Okay. Thank you for the heads up. I'll do just that. 1 Like |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by dfo12(m): 7:19pm On Jul 20, 2021 |
lovelybobo: Thank you. I appreciate you. |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 9:24am On Jul 21, 2021 |
THE BEGINNING OF DATA SCIENCE JOURNEY Part 8 Course 8: - Mathematics, Statistics and Probability Mathematics: Some people love it while others hate it with passion. It was taught in Nursery school, Primary school, Secondary school and University and yet most people just memorized formulas to pass their exams. That narration is about to change because behind every mathematical formula or concept is a solution to the problems of humanity. Do you know that linear regression is based on Gradient or Slope in mathematics while business model optimization is based on Differentiation in Calculus and many others like that. Your duty is to find out what models are related to what topics. You will study the principle of the topic and how it relates or affects your models. Things to learn in Mathematics 1 Linear Algebra 2 Calculus 3 Discrete Mathematics 4 Graph Theory 5 Information Theory etc Statistics: The field that deals with data and how they are used. This is one field you must be a master in to make head way in your career as a data scientist. Things to Learn in Statistics Everything is needed to be good at what you are doing, from inferential statistics to hypothesis formulation and testing, Principal component Analysis, Data collection methods, Population size, Interpretation of statistical results and many other things. You must be very good in statistics to be a good Data scientist. Probability: the science of uncertainty. whenever there is any doubt about an event occurring, probability is in place. The concept of probability is involved to estimate the likelihood of an event occurring. Example: It is 40% likely that it will rain tomorrow, if it rains tomorrow, you will be fine and if it did not rain you will still be fine since you have said the likelihood of raining is 40%. Things to learn in Probability 1 Probability space 2 Random variable 3 Probability rules 4 Expectation 5 Variance and Covariance 6 Probability Distribution etc Note: Mathematics, Statistics and Probability are the backbone of any model you hope to use. You must master them to be successful. Key takeaways You will be most effective working as Data analyst while studying to become a Data Scientist Studying for Data science without working real time with data will not yield much for you. 70% to 80% of your role as Data scientist will involve data cleaning and preparation. Know data cleaning, data wrangling and data preparation and know peace as a Data scientist ......To be Continued...... 4 Likes 1 Share |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by Najdorf: 6:08am On Jul 22, 2021 |
Well detailed thread |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 11:33am On Jul 26, 2021 |
Part 9 Course 9 : Big Data, NoSQL, Big Data Ecosystem Tools and Frameworks and Cloud Services Big Data: This is the term that describes the large volume of data and this data can be structured or unstructured. These type of data is been generated by businesses on daily basis. Big data can be analyzed for insights that lead to better business decisions and great business strategic moves. The key concepts guiding Big data are 1 Volume 2 Velocity 3 Variety 4 Veracity 5 Value NoSQL: [/b]This is database that provides a mechanism for storage and retrieval of data that is modelled in a different method other than the tabular relations used in relational databases. You do not need to define the structure of the database before its usage. Example of NoSQL Databases are: 1 Google MongoDB 2 Apache Cassandra 3 Amazon DynamoDB 4 Apache CouchDB etc [b]Big Data Ecosystem Tools and Frameworks: There are several tools and frameworks for handling and processing big data. It takes care of all the stages needed to effectively process and analyze your big data until desired result is achieved. Examples are: Apache Hadoop, Apache Spark, Apache Hive, Apache HBase, MapReduce, Apache Impala etc Cloud Services and Computing: Considering the volume and requirement for handling and processing big data, Having the knowledge of cloud services and computing might be needed in your tool box to effectively navigate the big data field. .......To be Continued......... 1 Like |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by munstaqq: 1:16pm On Jul 30, 2021 |
Please I'm having issues installing both MySQL and Tableau on my system. Below is what's showing on the screen. Please help!
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Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 5:45am On Aug 02, 2021 |
Data Analyst Project Example for Portfolio This is provide ideas, guidance and inspiration on those hoping to embark on personal project for their Data analyst portfolio Nairaland Politics project Background of the project: Nairaland is a Discussion forum where people come and share their thoughts on different topics. The site is divided into categories and sections to guide the users. Scope of the project: This project shall focus on the first 300 pages of the politics section of nairaland.com Project Questions: 1 What is the topic with the highest number of views 2 What is the topic and original Poster of the topic with the highest number view 3 What is the topic and original Poster of the topic with the highest number of comments or updates 4 Which post was last updated and when in the 300 pages scraped or oldest in terms of update 5 Who are the most active users in the politics section of Nairaland and how many topics did they create 6 Which month had the highest number of Headings 7 Any other question that can help us understand the data very accurately Project Task: task 1 : Write a python script to scrape 300 pages from politics category of nairaland.com task 2 : using necessary libraries clean and analyze the data task 3 : present your result using suitable visualization Skills demonstrated in the Project : 1 Web scraping 2 Regular expression usage 3 Writing to a file 4 Data manipulation 5 Data cleaning 6 Data visualization 7 Research 8 Documentation Column name definitions for the project : 1 Heading : The title of the thread 2 Poster : The person that created the thread 3 Updated : How many times contributions have been added to the thread 4 Viewed : How many people opened the thread to read the content without contribution 5 Time : The time and date the last contribution was made on the thread 6 Last_Updated : The lasted person to make contribution to the thread https://github.com/brightonu/portfolio_projects/blob/main/politics_project_Final.ipynb 3 Likes |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by lovelybobo: 9:10am On Aug 06, 2021 |
Are data scientist jobs competitive? Nope. Not at all. The truth is only a few people understand enough to work the end to end machine learning pipeline. Most applied data science is machine learning. Most machine learning supervised. Most supervised machine learning requires a heavy data cleansing component. Here’s the machine learning pipeline. [img]https://qph.fs.quoracdn.net/main-qimg-2b108963c13a0ba3a4f7652a0317610d[/img] Many that have the first two often lack the math and stats needed for number three. Many that have the math and stats in the third step lack the skills for the first two. Visually, the pipeline looks simple. In reality, it takes years of knowledge and experience to be able to work through the entire process from start to finish. When you’re ready to learn real-world machine learning. You’ll never secure a top paying real world job without being able to cleanse your own data. Source: https://www.quora.com/profile/Mike-West-99 1 Like |
Re: Data Analyst/science - The Smart Way To Learn And Be Effective by MXray: 2:00am On Aug 08, 2021 |
Man! This is so amazing! I hope to be as knowledgeable as you are soon. I started learning Python in May then stopped in June and picked up again in July. So far, I've learned Basic Python, Numpy, Pandas, Matplotlib, and Seaborn, also I have piggybacked to do a crash course on SQL, installed MySQL and practiced my SQL statements, and created some basic databases. I did the same for Excel, another crash course. I have also gone back to refresh my mind on Linear Algebra, especially Matrice and Vector, I did this so I could understand Numpy better. So far, I am picking up datasets on Kaggle, trying to do Exploratory Data Analysis on them. However, I do have challenges cos, I'd pick a dataset and would not know the questions to ask myself about the data. I've learned that it's not just about having the skills, if you don't know the questions to ask on your dataset, you will not know the answer to expect to get from it... Your thread has given me a new lifeline, I just followed your link to GitHub to see what you did with the Nairaland Politics project, and I'm so full of admiration for you... I hope to condense my disarrayed skills together by month end and hopefully be presenting my projects here... Thank you for the inspiration! 3 Likes |
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