¿Cómo se mantiene al día con las últimas tendencias y desarrollos en datos y análisis?

To ensure I'm at the forefront of data and analytics trends, I engage in continuous learning through industry events, webinars, and networking opportunities. I avidly follow leading publications and thought leaders, incorporating their insights into our talent acquisition strategies.

I listen to podcast to stay current. It is an easy thing to do on your commute. I listen to 3 most often although I know there are many more out there. My favorites are Chad and Cheese, Recruitment Flex and Recruiting Future. One out of the US, one out of Canada and one from the UK. A nice mix.

I'm a big supporter of staying connected with industry folks on Reddit and LinkedIn. And keeping up with the evolving field through online courses on platforms like Coursera. It's not just about staying informed; it's about being part of the conversation and enjoying the journey of continuous learning.

In my opinion, staying up to date on the latest data and analytics trends is critical. I looked at industry publications on frequently, follow trustworthy blogs, and receive newsletters. In addition, enjoy attending webinars and conferences to learn from experts. Participating in online forums and communities allows me to share ideas and stay up to date on real-world applications. Overall, this multifaceted approach enables me to develop well-rounded perspectives on emerging trends and effectively apply them in my work.

Staying ahead with data & analytics is key! I allocate 10 hrs monthly to professional development, diving into the latest industry reports and attending at least two webinars or conferences quarterly if possible. I've partnered with internal analytics team, and spearhead quarterly innovation labs within my TA team, leading to a 20% increase in the efficiency of our analytics tools. I also subscribe to leading HR analytics newsletters and have implemented a 'share-and-learn' session bi-monthly where my team discusses fresh insights, contributing to a 15% improvement in data-driven decision-making. These steps ensure we remain at the forefront of leveraging data for strategic talent acquisition.

For me, nothing works better than personal dialogue. Whether it's attending an in-person event to hear the latest news and views from practitioners or connecting on a 1-2-1 basis to ask those on the "frontline" what's interesting and exciting them, I find it easier to understand and follow what's coming when I hear it articulated with context by expert practitioners.

Read industry publications and blogs: Subscribe to industry publications and blogs that cover data and analytics. This will inform you about new technologies, best practices, and emerging trends. Some popular publications and blogs in the data and analytics space include Harvard Business Review, Forbes, MIT Technology Review, and Data Science Central.

Subscribe to Newsletters: Sign up for newsletters from leading data and analytics publications like Data Science Central, KDnuggets, and Towards Data Science. Read Journals: Regularly read academic journals and whitepapers from institutions like IEEE, ACM, and other research organizations.

Take online courses and tutorials: Online courses and tutorials are a great way to learn about new technologies and techniques in data and analytics. Many of these courses are available for free or at a low cost. Some popular online learning platforms for data and analytics include Coursera, edX, Udacity, and DataCamp.

Platforms: Utilize platforms like Coursera, edX, Udacity, and LinkedIn Learning for courses on the latest technologies and methodologies. Certifications: Earn certifications in specific tools and methodologies to enhance your knowledge and credentials.

Webinars and Conferences: Attend webinars, virtual conferences, and meetups to learn from experts and network with peers. Workshops: Participate in hands-on workshops that focus on practical applications of new tools and techniques.

Take online courses and tutorials: Online courses and tutorials are a great way to learn about new technologies and techniques in data and analytics. Many of these courses are available for free or at a low cost. Some popular online learning platforms for data and analytics include Coursera, edX, Udacity, and DataCamp.

Recently, I attended a virtual workshop on data storytelling, and it completely changed the way I present my findings. The ability to connect with industry experts and peers, even virtually, has opened up so many new opportunities for learning and collaboration. I highly recommend checking out events like Data Festival or Data Natives for anyone looking to stay ahead in the field. What are your go-to online events for keeping up with the latest trends?

My best recommendation for this is to become an Excel expert, first and foremost. Especially if it’s the main data source that will be feeding into the other different tools. In a previous job I had to learn about a long list of formulas needed to cleanup my datasets before they were even ready for Tableau. In grad school as well I had to learn how to use R and R Studio for a few classes, and basic coding knowledge was definitely a needed key skill. These simple steps will help you to navigate the tools more easily and understand more about what you’re looking at if you’ve never used them before.

Hands-on Practice: Regularly use and experiment with new data analytics tools and software. Platforms like Kaggle provide datasets and competitions to practice your skills. Open Source Projects: Contribute to open-source projects to gain practical experience and collaborate with the community.

Use data in your work from day 1 (you can also start today) and see how it starts providing you with insights almost automatically. Just make sure you base your data collection on meaningful metrics that are actual for the nature of your work and before you know it you will be more confident in making decisions. Explore which tools make it easier for you to visualize data. Use basic ones that come with your work toolkit like Office365 suite or just the free ones like Google Sheets that can also become powerful if used wisely. Explore courses / articles to give yourself direction but don't drown in endless tutorials, just start collecting, recording and transforming your data to get results quick, then learn new approaches, and iterate.

I had to learn PowerBI and Tableau last year for a project I was leading back then. I learned to perform data cleaning, modeling and presentation with those tools. I didn't and still don't consider myself experts. But my experiment with tools was valuable. Among all the benefits, I valued it the most that I can understand data analysts' "working languages" and our partnerships will be more efficient.

I remember starting out with Excel, and it really helped me grasp the basics of data structures and analytics. As I got more comfortable, I moved on to tools like Tableau and Power BI. These made it so much easier to visualize data and share insights in a clear, impactful way.

Stay updated on data and analytics trends by reading industry publications, following news feeds, monitoring professional networks, and reviewing updates from major conferences and tool providers.

Contributing to the industry by maintaining a personal blog where you can share your thoughts and observations on emerging trends in Data and AI. Establishing and managing a LinkedIn User Group dedicated to fostering a community around Data and AI, facilitating knowledge exchange and networking opportunities.

For me, following thought leaders, especially leaders who talk in a way you understand and can resonate with, is critical. We all learn in different ways, so finding someone who shares updates in a way that you can absorb information. There is so much information out there that it is easy to find overwhelming. You can’t be an expert in everything, so take it down to bite-size chunks and, importantly, make the time to learn about new things. We often feel at work, this is a luxury and we prioritise day-to-day activities ahead of this; however, learning new things is an investment in yourself. Prioritise this, prioritise you.

My best advice is to stay engaged in the community and always be willing to learn! I regularly attend webinars, virtual conferences, and other meetups to learn from industry experts and peers. Talent sourcing is always adapting with the market and candidate pools, so staying knowledgeable and being willing to try new approaches, even if they fail, is key to success. This proactive approach ensures that I am always up-to-date with the latest trends and developments in data and analytics.

One thing that often gets overlooked in data and analytics is the human element. Sure, we’ve got incredible tools and insights at our fingertips, but what really makes the difference is how we connect that data back to people. For example, using Polynize, I’ve seen how creating simulations of the actual job can transform raw data into stories—revealing a candidate’s problem-solving skills or adaptability in a way that resonates with both hiring teams and candidates. It's a reminder that data isn’t just about numbers; it’s about uncovering potential, driving engagement, and making the process more human at every step."