How can you transition into a BI query career from a non-tech field?

We can see every piece of data with information and meaning since I am a commerce graduate. I mostly paid my time on R&D towards understanding BI terminology. After that, I understood that we can create insights from Data for that need to learn some analytical specific tools. I delved into my self-learning at first Excel covering some advanced analytical functions and then moved into Microsoft Power BI and learned SQL. Since we have to make processes automated then I learned Microsoft Power Automate to streamline projects.

Transitioning into a Business Intelligence (BI) query career from a non-tech field is possible with strategic steps Gain proficiency in tools like Power BI or Tableau. Take relevant online courses and certifications. Learn about databases and basic data concepts. Develop foundational SQL skills for querying. Connect with BI professionals for insights and opportunities. Showcase BI projects in a portfolio. Gain experience through freelancing or volunteering. Highlight non-tech skills applicable to BI roles. Look for entry-level BI or data analysis positions. Seek internships in BI roles. Stay informed through online forums and blogs. Tailor your resume for BI positions. Commit to ongoing learning in BI field & seek Mentorship.

I appreciate lot of folks who have given so much idea about this. My opinion is that I have been working with many co workers who does not have a tech degree or certificate . Still they are well doing in BI field not only visualisations also they are well versed with the source data , optimization SQL query and advanced function. So , there is no bias here who is coming from tech or non tech field . If he /she get good training and little bit mentorship they can do it like experience person and can transition from non tech to BI career.

In my opinion, anyone can transition into BI career from non-tech background as long as one is willing to learn new skills. One should learn SQL, Data engineering and analytics concepts, Exploratory data analysis, popular BI tools, Python, some open source tools etc. Tech skills can be acquired from various online courses and most of them are available free. Experiential learning is must - try and solve real world problems BI projects are done to solve a business need...so understanding business is important

One should begin by understanding how businesses work, learn business terminology, engage with departments, and explore industry specifics. Then, master data management, analytics tools, SQL, and data modeling. Lastly, nurture your creative side with UI/UX design, data visualization, graphic design, and attention to detail. These essentials form the bedrock of a solid BI start. Access the gaps in your career by regularly assessing your skills and identifying areas for improvement, while also taking online challenges and participating in conferences to stay updated. To master this craft, don’t hesitate to get your hands dirty with real data, and seek feedback from industry experts to refine your skills and insights further.

Diving into BI (Business Intelligence) queries is like learning to fish in the digital ocean. Start with popular 'fishing tools' like SQL or Python. There are tons of online resources, from courses to podcasts, that teach you how to use these tools. It's like learning fishing techniques from experts! Plus, there are online 'fishing spots' where you can practice, using datasets to run queries and analyze data. So, grab your digital fishing rod and start catching insights! ?? #DigitalFishingForData

To break into BI, begin by leveraging your company's data for your current role. eg, If you are a financial analyst, start by requesting access to the main tables of your ERP and dig into it. Understand their relationships and master querying is the first step. Once you are familiar with how the tables are modelled, and you have created your own queries to support your adhoc reports, you could now start building a dinamic dashboard to suport not only static reports, but dinamic reports whow will answer multiple questions and where you would be able to slice and dice the information as you wish. For this second part, learning basics of dimension and fact and how to use a BI tool (tableau, power bi or qlik) would help a lot in your journey.

For people who are tansitioning into a business intelligence (BI) career from a non-tech field , I would recommend to develop a solid knowledge in Data concepts, such as metadata, data model, datatypes and forth. Then focus on Languages such as SQL and Python, tools & technologies like ETL tools such as DataStage and Talend, Data Visualization tools like PowerBI & Tableau. Having the fundamentals concepts will lead you to a deeper understanding of how technically you can solve Business Problems.

Many individuals often find themselves caught in a loop of confusion and numerous questions "What should I learn?", "Where should I learn it?", and "How much do I need to learn?"... I, too, have experienced this never-ending cycle of questions. Sometimes we overthink rather than put things into action. The most common Programming language or tool used in BI SQL, Power BI/Tableau, Python, and Excel. I suggest starting with just one or two of these tools or languages. Learn the fundamentals(Mastering Core concepts), Practice different scenarios Participate in different challenges, Be active in the community, Connect with experienced people in related fields and Learning from their experiences can provide invaluable insights and guidance.

Mastering BI(Business Intelligence) queries and Data Modeling is essential. Start with SQL, Python, or Power BI. Countless online resources like Microsoft Learn, provide foundational knowledge and practical application. Utilize datasets, challenges, and online platforms to hone your skills in data analysis, query writing, and report creation.

With a background in Finance and Accountancy, which is non-technical in nature, my portfolio has become an essential tool for distinguishing myself and demonstrating my proficiency in BI. To effectively showcase my work, I've utilized GitHub to establish a personal website where I can readily share my BI projects (Free). Some People find it difficult to obtain data, We can use platforms like Kaggle, GitHub, or even our Personal data or participate in online challenges that are conducted by different companies on LinkedIn. Furthermore, LinkedIn serves as an effective avenue for sharing these projects, allowing us to effectively showcase our skills and knowledge to a wider audience.

When making the shift from a non-technical position to the role of a Business Intelligence (BI) analyst, I discovered a valuable approach that greatly aided me in demonstrating the relevance of my existing business background to bolster the projects in my portfolio. A definite advantage that non-technical professionals can leverage is their wealth of expertise and their ability to seamlessly translate this business acumen into valuable support for decision-making processes. In my perspective, this capacity to bridge the gap between non-technical insights and data-driven decisions is what truly sets non-technical individuals apart and provides them with a distinct advantage in the BI realm.

Transitioning to the BI domain when you lack direct experience can indeed be a formidable challenge for non-technical professionals. The most straightforward path to overcoming this obstacle is by cultivating connections within the industry. Networking with established professionals is a powerful means of building trust and entering the BI domain. Despite possessing relevant skills, Non-technical professionals often find themselves overlooked due to their limited work history in the field. This is precisely where networking becomes invaluable, as it opens doors to opportunities that might otherwise remain closed.

So, why should you choose BI as career starter? With BI, you gain a deep understanding of how data influences operations, strategy, and decision-making. And when the time comes to explore new horizons in data science or data engineering, you’re more than ready. Data scientists rely on your data manipulation prowess, building upon it with advanced analytics. Data engineers find a kindred spirit in your ETL expertise, using it to construct robust data pipelines. BI offers a unique blend of essential tech skills, business acumen and design, striking a balance that’s neither overly complex nor overly simplistic. This equilibrium is perfect for early career professionals seeking to grasp the intersection of technology and business.

Transitioning to a BI career from a non-tech background? It's like teaching a penguin to cha-cha, but it's doable! Assess your skills, learn BI basics, master SQL and data visualization, embrace data warehousing, gain domain knowledge, build a portfolio, network, and apply for entry-level roles. Keep learning and develop soft skills. Remember, it's not rocket science; it's BI

SQL is a must but having a strong grasp of basic computer science concepts is extremely important. If you didn’t like Algebra word problems, you probably won’t enjoy doing BI. In this role you are a little bit Business Analyst, a little bit Data Architect, a little bit DBA (understanding how joins work is essential), a little bit quality assurance and a little bit artist as you work out visualizations. I encourage anyone wanting to make this transition to take a computer science 101 class and learn the very basic fundamentals. Knowing basic debugging techniques and order of operation concepts are important.