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All Episodes

TAG Data Talk — 76 episodes

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Title
1

Applying AI Technologies for Business Operations

2

The challenging nature of making everyone an AI expert

3

Leveraging AI to optimize energy consumption of renewable energy

4

Exploration of When and Where to Leverage GenAI in Knowledge Work

5

AI in the Real World: Balancing Innovation & Risk in a Regulated Landscape

6

Back to basics: Essentials for Product Development in the Age of AI

7

AI for the Rest of Us

8

Analytics Challenges Specific to the Manufacturing Sector

9

The Criticality of Mature data and AI for Accurate GenAI

10

How AI Impacts How We Develop and Grow Data Teams

11

Leveraging AI Technology in Healthcare

12

Getting the Absolute Best Data Science Talent to Solve Marketing Problems

13

The Role of the CAIO

14

Reducing Barriers to Complex Data Science Entry by Leveraging AI

15

Defining and Adapting your Data Science Career

16

Building Data Science and AI Capabilities to Last

17

Applying a Data-Informed Approach to Influence Leaders and Business Decision-Makers

18

Evolution of Data Science: Enhancing Productivity, Not Replacing You

19

Ensuring Scalable Data Science Solutions

20

Successfully Leveraging AutoML to Solve Complex Problems

21

Getting the Education Right: Choosing academic programs to stimulate a successful career in data

22

Building and Managing the Data Science Product Development Process

23

Evolution of Data Scientists: The Transitioning Role of Data Scientist

24

Dispelling the AI Hype

25

Developing and delivering a quick data science project

26

Enabling an Analytics Culture through Transformative Processes

27

Leading Data Scientists

28

Power Up with Data

29

Leveraging Data Science for Actionable Insights

30

Connecting and Leveraging Academic Partnerships in Data Science

31

Unlocking Data along the Value Chain in Manufacturing

32

Identifying the Why Why: Strategies to understand true problems and questions for data science projects

33

Building and Advancing a Data Science Career

34

Aligning IT data function with data science efforts

35

Data Science and Artificial Intelligence from a CTO's perspective

36

The Many Faces of Data Science

37

Enabling AI Efforts by Improving Data Governance

38

Enterprise Data Literacy to Scale Analytics Solutions

39

Making Analytics a Business as Usual Function

40

Data Ops for Dynamic Business Needs

41

Importance of Involving Analytics Stakeholders Early

42

Advanced Analytics for Financial Functions

43

The Lost Art of Listening for Improved Analytics

44

Leveraging Workforce Analytics for Strategic Advantage

45

Stimulating Data Science Innovation

46

The Value of Imperfection: Embracing the Realities of Model Building

47

Landing a career in the AI field

48

The Criticality of Understanding Business Context in Analytics

49

Encouraging Model Adoption among the Executive Suite and Beyond

50

Data Management in a Global Marketplace

51

The Importance of a Data Science Community

52

History, Future, and Concerns with Artificial Intelligent Solutions

53

Measuring the Effectiveness of Data Science Solutions.

54

Application of Data Science for Cause Based Initiatives

55

Data Science for E-Commerce

56

Human Behavior Side of Data Science

57

Creating a Data Mindset

58

Application of Data Science for Cause Based Initiatives

59

Understanding Data Science Skillsets and Roles

60

Forming Solid Business and Analytics Partnerships

61

True Understanding Versus Prediction in Data Science

62

Bridging the Academic - Industry Gap: Applying Analytics Principals to Problem Solving

63

Strengthening Your Analytics Offerings

64

The Last Mile of Analytics: Successful Consumption of Results

65

Advancing Analytics Capabilities

66

Balancing Offensive and Defensive Analytics Strategies

67

Applying Analytics to the Changing World of Media

68

Encouraging Analytics Adoption in the Executive Suite

69

Advancing Data Literacy

70

Organizing and Developing Successful Data Science Function

71

Framing Business Problems for Analytics

72

Effectively Communicating Analytics Results

73

Digital Transformation & the AI Revolution

74

Making Analytics Actionable

75

Marketing Analytics to Drive Customer Centricity

76

Developing a Data-Inspired Culture