
Join this 2-day live, online workshop Data Preparation and Quality for AI and Analytics. In this workshop, Dr. Prashanth H. Southekal will do an in-depth exploration of the DARS framework (Define-Assess-Realize-Sustain), a combination of strategic and tactical elements to help organizations acquire and sustain quality data for improved business operations, compliance, and performance management necessary for successful AI and analytics implementation. Whether you’re a data scientist, data quality specialist, analyst, business professional, or organizational leader, this course equips you with the skills needed to unlock the true potential of your data. Get ready to elevate your data preparation and quality, and set the stage for successful AI endeavors!
Companies that are data-driven have demonstrated improved business performance. McKinsey says, data and analytics can provide EBITDA (earnings before interest, taxes, depreciation, and amortization) increases of up to 25%. According to MIT, digitally mature firms are 26% more profitable than their peers. Forrester research found that organizations using data for decision-making are 3X times more likely to achieve double-digit growth. Hence every company today is looking at leveraging data for improved business performance. But most organizations are impaired with poor data quality. A HBR study found that just 3% of the data in a business enterprise meets quality standards. According to Experian Data Quality, poor data quality impacts up to 12% of revenues. Hence enterprises are looking at strategies and solutions based on practical guidance and proven solutions to derive quality business data in preparation for AI and analytics execution.
This training has 3 key learning objectives:
Two-Day Seminar Price:
Last day to register: Sunday, August 25, 2024
Seminar CEUs: 10
Seminar Date: August 27 – 28, 2024
Seminar Time: 11 AM – 3 PM Eastern / 8 AM – 1 PM Pacific
Who Should Attend?
This two-day, live, online workshop is intended for business and IT professionals at all levels who have been tasked with understanding and implementing AI and analytics on behalf of their organization. It does assume general business knowledge, but not specific technical knowledge or experience. It is appropriate for executives, departmental and/or project managers, data and enterprise quality specialists, consultants, analysts, data scientists, data engineers, and technical staff. The course is not designed for any specific business domain, and as such is applicable to any business function that is in need of more reliable information, such as finance, manufacturing, human resources, analytics, operations, and more.
The 3 basic requirements to enroll for this course are:
We offer several bulk licensing options for corporate and group use.
Contact us for a follow-up discussion!
Seminar Format
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