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AI and Data for Managers
Upskilling Workshop

20 Academic Hours, Face-to-Face or Online

Leverage data and AI for smarter decisions - no coding needed

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¿Por qué inscribirse en este taller?

Managers who know how to interpret data and leverage AI gain a clear advantage in making smarter business decisions. 

This instructor-led workshop equips managers and decision-makers with the skills to confidently work with data, dashboards, and AI tools – without needing to write code. Participants learn how analytics creates business value, how to ask the right questions, and how to turn insights into effective actions. 

Through hands-on exercises, discussions, and real-world case studies, the workshop also strengthens analytical thinking, improves the ability to interpret reports and dashboards, and helps managers collaborate more effectively with data teams while using AI in the decision-making process.

By enrolling in this workshop, you’ll sharpen your decision-making skills, learn to turn data into clear actions, and confidently navigate AI-driven business environments.

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¿A quién va dirigido?

Este taller es ideal para:

  • Leaders, managers, and decision-makers
  • Professionals who create reports, dashboards, and analytics to guide decisions
  • Non-technical professionals who want to use data and AI without coding

Requisitos previos

  • Basic business or managerial experience
  • Familiarity with business reports, dashboards, or performance metrics
  • Interest in using data and AI to support better decision-making

Objetivos de aprendizaje

By the end of this workshop, participants will:

  • Understand how analytics creates business value and what to expect from data and dashboards
  • Interpret reports, charts, and dashboards critically to identify trends, risks, and inconsistencies
  • Choose the right tools and outputs (e.g., Excel, BI, automation) for different business questions
  • Collaborate effectively with analysts and use AI tools to generate insights
  • Translate insights into clear decisions, follow-up analysis, and actionable plans

Lo que obtendrá...

  • 20 academic hours of training in 5 face-to-face or online sessions with a professional instructor, teaching in English
  • Instruction, guided analysis of reports, charts, and dashboards, AI-assisted practice, and managerial discussions
  • Certificado de graduación de Wawiwa, incluido uno digital para LinkedIn
  • Pertenencia de por vida a la comunidad global de antiguos alumnos de Wawiwa, formada por profesionales de la tecnología de todo el mundo.

Supervisor profesional

This unique workshop was built by a professional team made up of the leading experts in data and AI, with vast knowledge and experience in training too.
Talía Morchi

Talía Morchi

Jefe de Programas de Análisis de Datos

Talia cuenta con más de 10 años de experiencia en el sector de las TI, habiendo desempeñado las funciones de gestora de productos, gestora de proyectos y gestora de soluciones de datos, donde se especializó en el análisis de datos, además de otras responsabilidades.

Es profesora en la Universidad Bar Ilan, donde dirige el curso de Desarrollador de BI y también imparte clases en el curso de Ciencia de Datos. Además, es profesora de pregrado en Ono y directora académica y profesora principal del curso de analista de datos en la G-Academy.

Talia es experta en varias herramientas de desarrollo, como SQL, Python, Excel y uniPaaS.

Talia es licenciada en Informática con Economía y Gestión por el Colegio Académico de Tel Aviv, Yaffo.

Programa del taller

Module 1: Data, Analytics, and Managerial Decision-Making (4 Hours)

  • Why analytics matters: business value, risks, and common misconceptions
  • Roles in the data ecosystem: Data Analyst, Business Intelligence (BI), and Data Engineering – what each role delivers
  • Data collection vs. data analysis: why more data does not automatically lead to better decisions
  • Framing the business question: defining objectives, constraints, and Key Performance Indicators (KPIs) that guide the analysis
  • Common managerial mistakes when working with data and how to avoid them

Hands-on: Make a decision using partial data, identify what information is missing, and draft the next analysis request.

Module 2: Understanding Analysis Results (4 Hours)

  • How to read reports, charts, and dashboards critically: trends, anomalies, baselines, and comparisons
  • Segmentation and data cuts: time, region, product, channel, and customer type
  • Correlation vs. causation – and how misinterpretation leads to poor decisions
  • When data misleads: situations where “good-looking” metrics still harm the business
  • Contradicting indicators: managing KPI conflicts and trade-offs

Hands-on: Analyze a mini dashboard, identify insights and risks, and define follow-up questions.

Module 3: Data and Visualization Tools from a Manager’s Perspective (4 Hours)

  • The tool landscape: Microsoft Excel, Power BI, SQL, Python, and automation tools – who uses them and why
  • Excel as a managerial tool: quick analysis, pivot tables, and simple dashboards – strengths and limitations
  • Power BI for multidimensional analysis: when Excel is not sufficient, governance considerations, and data refresh cycles
  • Risks of blind reliance on dashboards: metric definition drift, missing context, and incorrect filters
  • Choosing the right tool and output for a business question – and how to brief the analytics team effectively

Case study + hands-on: Analyze the same business problem using Excel and Power BI – compare insights and resulting decisions.

Module 4: People, Data, and Artificial Intelligence (AI) in the Organization (4 Hours)

  • What makes a strong Data Analyst: analytical thinking, communication skills, business understanding, and professional integrity
  • How managers and analysts work best together: briefing, review, iteration, and alignment around decisions
  • AI in analysis and decision-making: where it helps, where it can mislead, and what needs validation
  • Using AI tools as a manager: clarifying metric definitions, generating hypotheses, summarizing findings, and drafting decision briefs
  • Boundaries and responsibility: confidentiality, compliance, verification, and human accountability

Hands-on: Design a workflow (people + tools + AI) for a cross-departmental use case.

Module 5: From Insights to Business Action (4 Hours)

  • Turning insights into decisions: evaluating options, assumptions, risks, and potential business impact
  • Prioritization frameworks: effort vs. impact, risk vs. reward, and quick wins vs. strategic initiatives
  • Validating decisions: leading vs. lagging indicators, experiments, and feedback loops
  • Embedding data into ongoing management processes

Bring It Together (BIT) project (industry-tailored): Participants produce a decision plan and draft a follow-up analytics request.

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