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
- Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics
- Larry Hall, Advanced Analytics Account Director, Pegasus Knowledge Solutions Inc.
- Dr. Chandra Bhagi, Data Science Architect, Pegasus Knowledge Solutions Inc.