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Becoming a Data Analyst in 2024 is more difficult than it was a couple of years ago. The competition has grown but so has the demand for Data Analysts! There are 5 areas you need to excel at to land a career in data. (so punny...) 1. Skills 2. Experience 3. Networking 4. Job Search 5. Education Let's dive into the first and most important area, skills. Skills Every data analytics job will require a different set of skills for their job description. To cover the majority of entry-level positions, you should focus on the core 3 (or 4 if you have time). - Excel - SQL - Tableau or Power BI - Python or R(optional) No need to learn any more than this to get started. Start learning other skills AFTER you land your first job and see what data analytics path you really enjoy. You might fall into a path that doesn't require Python at all and if you took 3 months to learn it, you wasted 3 months. Your goal should be to get your foot in the door. Experience So how do you show that you have experience if you have never worked as a Data Analyst professionally?  It's actually easier than you think!  There are a few ways you can gain experience. volunteer, freelance, or any analytics work at your current job. First ask your friends, family, or even Reddit if anyone needs help with their data. Second, you can join Upwork or Fiverr to land some freelance gigs to gain great experience and some extra money. Thirdly, even if your title isn't "Data Analyst", you might analyze data anyway. Use this as experience! Networking I love this section the most. It has been proven by everyone I have mentored that this is one of the most important areas to learn. Start talking to other Data Analysts, start connecting with the RIGHT people, start posting on LinkedIn, start following people in the field, and start commenting on posts. All of this, over time, will continue to get "eyes" on your profile. This will lead to more calls, interviews, and like the people I teach, job offers.  Consistency is important here. Job Search I believe this is not a skill and is more like a "numbers game". And the ones who excel here, are the ones who are consistent. I'm not saying you need to apply all day every day but you should spend SOME time applying every day. This is important because you don't know when exactly a company will be posting their job posting. You also want to be one of the first people to apply so that means you need to check the job boards in multiple small chunks rather than spend all of your time applying in a single chunk of time. The best way to do this is to open up all of the filters and select the most recent and posted within the last 3 days.  Education If you have a degree or are currently on your way to getting one, this section doesn't really apply to you since you have a leg up on a lot more job opportunities. So how else does someone show they are educated enough to become a Data Analyst? You need to prove it by taking relevant courses in relation to the industry you want to enter. After the course, the actual certificate does not hold much weight unless it's an accredited certificate like a Tableau Professional Certificate.  To counter this, you need to use your project descriptions to explain how you used data to solve a business problem and explain it professionally. There are so many other areas you could work on but focussing on these to start will definitely get you going in the right direction.  Take time to put these actions to work. Pivot when something isn't working and adapt. It will take time but these actions will reduce the time it takes you to become a Data Analyst in 2024

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✅Make your Python Learning Simple. 🧑‍💻Preparing for interviews are a pain , i know, i have gone through this and this is depressing , especially when you are switching from a non coding profile to a something like a data role. You can find lot of roadmaps on the internet , on what skills to acquire and learn to get a job into this field but when you start learning the concepts from those skillset you begin to know how big the ocean is and it is sometime, it seems impossible to cover everything in lets say 6 months too. 🤑Soo if you also relate to the above problem you need to read this entire post to make your python learning journey simple. ℹ️See i know PYTHON IS VAST i am not denying , but you need to prepare smart, But what does this mean ? This simply means that why are we studying PYTHON ? To get jobs right ? so if our target is to get a job and not be a professor of PYTHON why cant we just focus on concepts which are job relevant or interview relevant and are asked in the interviews. I bet even if you spend 2 year only learning PYTHON it will not gonna finish , so instead learn only topics relevant to your requirements. In the below screenshot, you can find essential Python Concepts. You can access essential Python Interview Resources here. Like for more ❤️

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Some basic concepts regarding data and database Data is representation of the facts, measurements, figures, or concepts in a formalized manner having no specific meaning. Database is an organized collection of the data stored and can be accessed electronically in a computer system. DBMS are software systems that enable users to store, retrieve, define and manage data in a database easily. RDBMS is a type of DBMS that stores data in a row-based table structure which connects related data elements. SQL is a database query language used for storing and managing data in RDBMS.

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Ways to improve the performance of Tableau 👉🏻 Use an Extract to make workbooks run faster. 👉🏻 Reduce the number of marks on the view to avoid information overload. 👉🏻 Hide unused fields. 👉🏻 Use Context filters. 👉🏻 Use indexing in tables and use the same fields for filtering. 👉🏻 Remove unnecessary calculations and sheets.