26 min
AI and the Democratization of Data of with Alonso Castañeda Andrade AI Live & Unbiased
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Dr. Jerry Smith welcomes you to another episode of AI Live and Unbiased to explore the breadth and depth of Artificial Intelligence and to encourage you to change the world, not just observe it!
Dr. Jerry is joined today by Alonso Castañeda Andrade, who is the Managing Director of Data Engineering and Analytics at Agile Thought. Dr. Jerry and Alonso are talking today about the role that Data Engineering and Analytics play in AI.
Key Takeaways:
Why is it a challenge today to create quality data products? Technically a lot of tools are available today for databases, the cloud allows us to scale quickly to be able to manage all the data, but most of the challenges come from the organizational aspect and processes, which involve the dynamic nature of the data. You can do AI without having data. Where do we start to create good quality data? Data is available in a variety of forms and places. Organizing data is a challenging job and tools are needed to assist the Data Engineer to perform his role, like having a good architecture platform for data and having a well-defined flow of information. Once we have the organized data, analytics can be run on them. What are customers looking for out of their dashboards? What are they really looking to get out of their analytic solutions? Data Engineering and Analytics are asked to work on the integration of systems. Customers expect their business to gain more visibility. Customers want to receive trusted data in a timely manner. The analytic team, dashboard engineers, and data scientists need to work together for better outcomes. The democratization of the data: How do we enable everyone in the company to have access to the data that they require, and do that by themselves without depending on others? Trends for 2022: The continuous migration to the cloud. Clouds play a very important role in the data modernization of platforms since they allow businesses to deploy data products faster (up to 50% velocity increase). Services become really significant, especially the cognitive services and analytical databases. Business requires their data as soon as possible when something happens, for example, five minutes in the banking industry for fraud can cost millions of dollars. What is going on today in the world of Data apps? One of the challenges is to provide the data that the business requires in a timely manner, generally traditional analytics have been waterfall in nature, bringing all the data to create a massive data model; many fail in this process since it is time-consuming and expensive, and once they are ready the data may be obsolete. Data is an asset of an organization and being able to make that into a competitive advantage is key.
Stay Connected with AI Live and Unbiased:
Visit our website AgileThought.com
Email your thoughts or suggestions to Podcast@AgileThought.com or Tweet @AgileThought using #AgileThoughtPodcast!
Learn more about Dr. Jerry Smith
Dr. Jerry Smith welcomes you to another episode of AI Live and Unbiased to explore the breadth and depth of Artificial Intelligence and to encourage you to change the world, not just observe it!
Dr. Jerry is joined today by Alonso Castañeda Andrade, who is the Managing Director of Data Engineering and Analytics at Agile Thought. Dr. Jerry and Alonso are talking today about the role that Data Engineering and Analytics play in AI.
Key Takeaways:
Why is it a challenge today to create quality data products? Technically a lot of tools are available today for databases, the cloud allows us to scale quickly to be able to manage all the data, but most of the challenges come from the organizational aspect and processes, which involve the dynamic nature of the data. You can do AI without having data. Where do we start to create good quality data? Data is available in a variety of forms and places. Organizing data is a challenging job and tools are needed to assist the Data Engineer to perform his role, like having a good architecture platform for data and having a well-defined flow of information. Once we have the organized data, analytics can be run on them. What are customers looking for out of their dashboards? What are they really looking to get out of their analytic solutions? Data Engineering and Analytics are asked to work on the integration of systems. Customers expect their business to gain more visibility. Customers want to receive trusted data in a timely manner. The analytic team, dashboard engineers, and data scientists need to work together for better outcomes. The democratization of the data: How do we enable everyone in the company to have access to the data that they require, and do that by themselves without depending on others? Trends for 2022: The continuous migration to the cloud. Clouds play a very important role in the data modernization of platforms since they allow businesses to deploy data products faster (up to 50% velocity increase). Services become really significant, especially the cognitive services and analytical databases. Business requires their data as soon as possible when something happens, for example, five minutes in the banking industry for fraud can cost millions of dollars. What is going on today in the world of Data apps? One of the challenges is to provide the data that the business requires in a timely manner, generally traditional analytics have been waterfall in nature, bringing all the data to create a massive data model; many fail in this process since it is time-consuming and expensive, and once they are ready the data may be obsolete. Data is an asset of an organization and being able to make that into a competitive advantage is key.
Stay Connected with AI Live and Unbiased:
Visit our website AgileThought.com
Email your thoughts or suggestions to Podcast@AgileThought.com or Tweet @AgileThought using #AgileThoughtPodcast!
Learn more about Dr. Jerry Smith
26 min