A continuación, le indicamos cómo puede aprovechar el análisis de datos para el futuro del análisis empresarial.

Sometimes, the major challenge is your data cleanliness. Many organizations currently processing manual reports data which has chances of erroneous data which doesn't make sense while doing analytics. It's crucial to have few experts in your team to handle these quality issues with ease.

Data mastery is essential on delivering information and providing insights for our stakeholders. By understanding what data you need to gather will help you provide more accurate reports and insights that can be useful in making your decisions. For example, In my case I need information if our company sales team is performing well on a specific time frame. I only gather data related to it so that I can focus on my objective. Therefore, without foundational understanding of data management and analysis, our ability to analyze and consolidate data accurately will hinders us.

To excel in business analysis, it's crucial to have a comprehensive understanding of data and adopt a strategic approach. Questioning the accuracy and context of data, collaborating with professionals from different domains, and being open to new tools and techniques are key. Adapting quickly to technological changes and communicating insights clearly and persuasively are essential. Mastering data involves critical thinking, interdisciplinary collaboration, continuous innovation, and effective communication, enabling anticipation and confident shaping of the future.

Yes, there was a time when people were relying majorly on their six senses for analysing many such datasets. Nowadays, there are a bunch of tools available in the market as well as the resources to learn them. Really they are making data analytics uncomplex.

According to me, there is a simple rule which I follow in my day to day data analytics role. - Investing 50% of the time in critical thinking without touching my system. - 10% in making the plan to proceed - 30% of the time in writing some code and analysing through tools. - 10% time to validate and cross check if it meets the actual target of analysis.

I see the analyst not just as someone who answers business questions with data, but as someone who delivers answers to questions that have never been asked. Know the business well, explore and question everything. As a consequence, the knowledge you can deliver will far exceed expectations. Refining these new insights with the team will solidify new business visions.

I agree. Your findings are only as impactful as your ability to communicate them. Sharpen your communication skills to ensure that you can convey complex data insights in a clear and understandable manner. Learn to tailor your messaging for different audiences, whether it's for technical teams, stakeholders, or non-technical staff. Effective communication helps translate data-driven insights into strategic actions that can be embraced by the entire organization.

Com certeza uma das etapas mais importantes, a maneira de passar a mensagem pode impactar tanto quanto a analise realizada, quando não se deixa a mensagem clara ou sem conclusões claras, diversas interpretações podem ser obtidas de uma mesma visualização, com isso é importante conduzir o público para a descoberta, de maneira objetiva e simples.

A few years ago, we would never have imagined that AI would be as advanced as it is now, and this has only become a reality due to the vast amount of data that is generated and processed. Today, we can no longer be conservative about evolution in the data field. This forces professionals in this area to seek increasingly up-to-date knowledge, as what exists and is used today may become completely obsolete in just six months. To move forward, constant updating is essential, in both software and hardware, as well as in personal knowledge, and this is evident nowadays. Seeking specialization through schools, courses, and new studies is a crucial option to stay updated.

On one occasion, I had to refrain from delivering a value analysis because the data contained some personal client information. This could potentially result in bias towards certain customer profiles, which is not appropriate in real-world client classification practices. In this case, opting for a more generalized approach becomes more ethical. By doing so, we uphold client confidentiality and legal compliance while still delivering valuable insights to the team.

It helps businesses understand trends, customer behaviors, and operational efficiencies. By analyzing data, businesses can make informed decisions, predict future outcomes, and identify areas for improvement. It allows companies to uncover hidden patterns and insights that can lead to better strategies, enhanced customer satisfaction, and increased profitability. Harnessing data analysis means using tools and techniques to extract valuable information from large datasets, enabling businesses to stay competitive and agile in a rapidly changing market landscape.