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Tristan Handy has been curating the Analytics Engineering Roundup newsletter since 2015, pulling together the internet's best data science & analytics articles. Tristan and co-host Julia Schottenstein now bring the Roundup to real life, hosting biweekly conversations with data practitioners inventing the future of analytics engineering. You can view full episode summaries and read back issues of the Roundup newsletter at https://roundup.getdbt.com. The podcast is sponsored by dbt labs, makers of the data transformation framework dbt. To reach our team, drop a note to podcast@dbtlabs.com.

Data analytics offer an incredible opportunity to predict the future, engage with new technological advancements, and gain valuable insights about your business. But unless you're staying on top of the cutting edge of analytics, your company is wasting that potential-and your competitors will be gaining speed while you fall behind. These articles by experts and consultants will help you understand today's essential thinking about what data analytics are capable of and how to adopt their use in your organization.

Unlocking the Power of Data: A Guide for Leaders and Executives" As a leader or executive, you know the importance of data in driving business decisions and staying ahead of the competition. But, with the increasing amount of data generated daily, it can be overwhelming to know where to start and how to utilize this valuable asset effectively. This blog, with multiple topics, addresses the technical terminology in data engineering and analytics on the cloud.

In our age of accelerating progress in so many fields, it’s easy to lose sight of the underlying innovation that makes the data analytics revolution possible. These 24 lectures introduce you to the key concepts, methods, and accomplishments of this versatile approach to problem solving. You need no expertise in mathematics to follow this exciting story. Tim Chartier, professor of mathematics and computer science, explains the basic computational techniques used in data analytics, but his focus is on how these ideas are applied and the amazing results they achieve.

From two pioneers in business analytics, an update of the classic book on how analytics and business intelligence are transforming competition and how leading organizations build and compete on an analytical capability. Leading companies are doing more than just collecting and storing data in large quantities - they're now driving their competitive strategies based on data-driven insights. In Competing on Analytics, Davenport and Harris explain how analytics are transforming the basis of competition in industry after industry.

With the world going remote, and data science following along, you can start and pursue a career in data right here, right now. How do I start? What do I need to know? What is data analytics? I'm sure one, if not all, of these questions have run through your mind. Well, the answer is data literacy: the ability to read, understand, and communicate data into information. Building a solid foundation of practical knowledge is the first step to being successful in data. From there, you can finally decide what direction you should go in and start gaining the required knowledge.

Innovation influences the market and its operators, especially about competition conditions. One of the most significant technological advances relates to the possibility of capturing a huge amount of information and processing them rapidly: two of the main features that make up the phenomenon known as big data. This not only entails the emergence of specialized operators in these activities, but also makes a "data economy" possible.

Explosion of the economic relevance of data is related to: first, technological progress that has drastically reduced the costs of collecting and storing data; second, the advances in analytic techniques that have allowed for more advanced processing to extract greater value from available data. So, more value is extracted from exhausted data. Information generated for one purpose can and should be reused for another one, which means that data moves from primary to secondary uses. Data are more valuable over time.

Cosa significa farsi guidare dai dati? Quai gli strumenti e gli approcci per trovare valore in una quantità sempre più complessa di informazioni? Raccontiamo la rivoluzione data-driven.