Here's how you can enter the field of Business Intelligence (BI) with a non-technical background.

Business Intelligence is all about How well do you understand the business? How much you can scale the business? How can you make the business sustainable? by utilising the knowledge of business and the data/information of the business. Coming from a non-technical background may feel difficult in the beginning until you get some required basic technical skills such as SQL, Excel, PowerBI/Sisense etc. And understanding the business. But it's just a matter of time to be in a good position or getting complete control over it. A small suggestion/change can turn into a great outcome. Every solution should be towards scaling the business and making it sustainable.

Entering Business Intelligence (BI) with a non-technical background involves strategic learning and skill-building. Start by understanding BI basics: data warehousing, ETL, visualization, and reporting. Learn tools like Excel, Tableau, Power BI, and SQL. Utilize online courses on platforms like Coursera and LinkedIn Learning. Gain practical experience through projects, open-source contributions, and internships. Network in BI communities, seek mentorship, and understand business processes across domains. Apply for entry-level roles such as data analyst or BI developer, emphasizing your analytical skills and project experience. Stay updated with BI trends and continuously improve your skills.

Ce qui m'a été utile lorsque j'entrais dans le monde de la BI, j'ai très vite compris que pour exceller dans ce domaine il me fallait une bonne dose de volonté, d'humilité pour pouvoir apprendre les bases de la BI et ensuite pouvoir s'entourer de personnes qui comprennent ce domaine. Le voyage ne débute réellement que lorsqu'on prend la décision d'entrer dans le monde de l'informatique décisionnel. Tout ce qu'il reste à faire c'est de prendre plaisir et de profiter de ce voyage sans fin.

Business intelligence (BI) refers to the tools, technologies, and practices used to collect, integrate, analyze, and present business information. The goal of BI is to support better business decision-making by providing insights derived from data. Key aspects of business intelligence include: Data collection and integration Data warehousing Data analysis and visualization Reporting and dashboards Performance metrics and KPIs Predictive analytics BI helps organizations: Identify business trends Measure performance Optimize operations Discover new opportunities Make data-driven decisions

I firmly agree with the statement “understand data warehousing.” This in turn does imply a good set of skills for SQL. In my experience mentoring others in BI, many focus on the mastery of functions and the benefit from the perspective of a single entity or data source. The power of BI is data modeling and proofing the assumptions and applications of data usage across data sources from separate systems. BI should improve your knowledge, ensure that you are asking the most pertinent questions, and aligning your data model to the decisions that need to be made.

Power Bi and Tableau are definitely game changers.Proficiency in developing dashboards gives you a competitive edge in the career market place for sure Also try to learn how other skills like Power Automate or Power App can be used together with Power Bi

Power BI et Tableau sont les leaders en termes d'outils BI non seulement en raison de leur facilité d'utilisation mais également en raison de leurs communautés d'experts de divers horizons qui sont toujours prêts à repousser les limites des fonctionnalités.

Au fil des années, il m'a été indispensable d'acquérir des compétences storytelling (pour communiquer sur les données que j'exploite), en SQL afin de pouvoir aisément travailler avec des bases de données de divers ordre aussi et surtout en langages de programmation tels que Python, Javascript et R.

Start by looking at what is available in making current decisions around you. Get a first-hand knowledge of the processes that go into those decisions. Look for gaps between sources that use offline processing and the refinements that are being made to data. Address additional insights that improve the decision. Construct these elements into a BI framework. Represent the decision outcome with visuals, metrics, and support data.

Il est crucial, afin d'être toujours performant dans le domaine de la BI, de participer à la veille technologique. Avec l'avènement de l'intelligence artificielle, nous gagnerons à combiner l'IA à la BI en utilisant chatGPT pour affiner nos recherches et gagner un temps fou et en utilisant Copilot pour gérer les données complexes lorsque nous utilisons Excel, PowerPoint etc.

Learn from your needs. As you explore BI and model development, there will be obstacles to what you are trying to accomplish. Do not shun from these obstacles or simply ask someone else for the solution. Identify where your problem is unique to the canned solutions you find online. Forge a solution that is robust and integrates in the simplest form with the least amount of work. This is usually the best solution.