Putting the Intelligence in Your Company’s Approach to Artificial Intelligence: It Starts with the Data
Webinar Speaker: Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics
Date: Wednesday, September 4, 2019
Time: 9:00 a.m. PT, 12:00 p.m. ET
One of the biggest trends in analytics is AI (artificial intelligence). At TDWI, we see numerous organizations looking to leverage AI technologies such as machine learning and natural language processing for a host of use cases. Although some AI initiatives seem futuristic, organizations are reaping significant results predicting churn and next-best-offer or employee attrition. The value of all of these use cases is real and can help transform organizations if done right.
A top challenge we see organizations facing as they make the move to use AI technologies is dealing with data. AI often involves using large amounts of disparate data, both internal and external to the organization. Data quality is a key issue. The old saying “garbage in, garbage out” applies to machine learning as well as other kinds of analytics. In fact, aside from lost revenue due to incorrect models based on bad data, poor data quality can reduce trust in the results of the analysis and even damage a company’s reputation.
One trend to help combat this problem is that AI technologies such as machine learning are being used in some newer products to help find issues in the data. This might include deduplicating data or looking for gaps, outliers, and anomalies in the data. These AI-infused tools can help organizations meet data quality goals of reasonableness, consistency, timeliness, and relevancy. To truly transform an enterprise, organizations often need flexible solution platforms and strategic partners to begin, accelerate, or expand their journey.
Join TDWI's VP of Research Fern Halper, along with recognized industry thought leaders from Pitney Bowes and Pegasus Knowledge Solutions, for actionable insight and best practices to deliver on the AI promise.
- What to expect and how to accelerate the journey
- Trends, use cases, and challenges for AI
- Pillars for a successful AI implementation
- How to ensure that your data can be easily cleansed, trusted, complemented, and governed for AI success
- How to drive an effective AI pilot and best practices for solidifying AI as a strategic initiative
- How to drive leadership buy-in – cost, timeline, teams, and requirements
Larry Hall, Advanced Analytics Account Director, Pegasus Knowledge Solutions Inc.
Larry Hall is Senior Consultant andAI and Machine Learning Evangelist at PKSI. He has spent a career in the technology industry as a user, developer and promoter of advanced technology solutions to help companies address their key business challenges. Currently, Larry serves as a Director at PKSI.
PKSI was founded in 1997 to help companies apply state-of-the-art advanced analytics technologies, including AI and machine learning, as a means of reducing costs, increasing revenue and improving competitive position.
Dr. Chandra Bhagi, Data Science Architect, Pegasus Knowledge Solutions Inc.
A techno-managerial professional having 24+ years of experience in IT industry and over 12+ years’ experience in designing and building Data Warehouses/Data Lakes, Business Intelligence, Data Architectures, Big Data, Data Analytics, MDM and related systems to various industries across North America and Europe.
In past, Bhagi worked with major American companies namely, Sun Microsystems, GE, Amazon.com and CSC. At CSC, Dr. Bhagi served the company thru multiple roles during his tenure of 9+ years; Before leaving the company he was Solution Executive for Zurich North America account, and also served as Global Capability Lead for Data Science and Visualization division of greater CSC. During this time, Dr. Bhagi was invited to join Big Data Analytics startup company ‘Data Cubes’ as CTO to lead /head the Engineering, wherein he played a vital role in building the product from conceptualization phase till go live with several customers in North America.
Dr. Bhagi has deeper roots in data analytics space, has designed, developed and managed multiple Data Analytics Products and Offerings for Insurance, Retail industry and Banking using Apache Hadoop open stack, Horton, NLP, Python, NOSQL/Hbase/Mongo, Java/SOA, AWS, S3/RDS, AngularJS/ReactJS/NodeJS Etc. Also, successfully delivered multiple large end to end Projects in a) DW/ETL (Informatica, BODS, SLT SSIS, Talend), b) BI (SAP BO, Micro Strategy, Brio, SSRS), c) Big Data/ Data Lake (Hadoop Open Stack), d) Data Sciences (Python, R) and e) and Data Visualization (Qlikview, Power BI, Tableau, Xcelsius).
Dr. Bhagi is M.Phil in Computer Science, M.S in Information Technology and has a PhD degree covering EDW/Data Analytics/BPM in the Banking domain. Dr. Bhagi also completed the ‘Marketing Analytics’ program from Cornell University.
Fern Halper, Ph.D.