Voici comment vous pouvez aligner votre plan de formation continue sur vos objectifs de carrière à long terme dans le domaine de l’analytique.

Considero muito importante para o crescimento de qualquer profissional interessado(a) numa carreira analítica: 1. Treinamentos em técnicas de análise com profissionais seniores e competentes irão abrir a sua mente e lhe dar alternativas de caminhos para ser bem sucedido(a) na carreira analítica. Mas desenvolver uma carreira bem sucedida em análise exige não apenas investimentos em treinamentos. 2. Networking: troque ideias com profissionais que agregam conhecimento. Frequente eventos e converse com as pessoas. Exponha suas ideias. 3. Seja autodidata e leia sobre diversos assuntos. Você não será um profissional analítico se debruçando apenas em livros técnicos. 4. Esvazie a sua mente. Pratique técnicas como meditação, yoga e chi kung

Focus on your first step. Analytics are everywhere today - so no matter the career you are aspiring to or the job you are looking for - you will be better equipped for it with an analytics edge. Evaluate if your career goals needs just a basic understanding or an in-depth understanding with special domain expertise.

There are various options - ranging from free videos to full-fledged undergraduate or graduate degrees, to everything in between like Analytics certificate programs - some of which are stack-able for an eventual degree.

Analytics is almost like "Medicine" in that it is an enormous domain - just about every human endeavor nowadays will require some level of Analytics. Thus, it's important to first identify what general market/area that you are interesting in working or studying. Then look at the nature of the data you will run into, and then determine what skills you may lack, since the type and character of the data will lend itself to different tools and therefore specific skills. A simple example is the difference between Graph databases, and Relational databases, like SQL. There are certain sets of data that are best racked using Graph databases. If the type of data you are interested in is Graph-like, then learn Graph queries and architecture.

When you select your courses and certifications, remember to create a balanced curriculum for yourself, wherein some of the courses are tactical and specific to platform and tools, and some are more foundational and general. The first provides skill-building with a specific set of tools that you can offer and which match job listings or requirements. The second is necessary for several reasons: 1) Specific tools come and go, but general understanding of analytical frameworks remain valid no matter what tools are used. 2) General courses provide the foundation necessary for you to apply that foundation using the tools. 3) You need to be able to speak generally in presentations and interviews.

Flexibility matters .... certificate programs that are stack-able might be advantageous if you are already working full-time.

Choose an agile program. Differentiate between "Data Analytics" programs or certificates vs. "Business Analytics" programs and certificates. Depending on your career path, one of them might be more useful than the other. Speak with potential employers in the field you aspire to be in to determine the best path forward. An agile program will always offer you the very best mix of foundational/technical programming blended with the latest applications from the industry.

LinkedIn can be used as a way to lay the groundwork for your career growth. Think long-term, and spend some time each week in career development through networking, primarily on LinkedIn, since it's probably the best platform for communication professionally these days. First, find an organization that is doing interesting work. Then find people in that org and are in analytics positions. Then pay attention to their posts, and begin by contributing to a thread. Keep it chill, not aggressive, but slowly establish a relationship, because at the end of the day, careers are grown through relationships, like everything else. Put in the time each week and this will pay off enormously over the course of months and years. Plus it's fun.