Course Introduction
Databricks SQL Analytics and Dashboarding Training Course provides a practical foundation for professionals who need to query, analyze, visualize, and communicate business data using Databricks SQL. Databricks SQL provides a cloud data warehouse environment built on lakehouse architecture, allowing analysts to query data directly in the lake while using SQL warehouses, dashboards, metric views, alerts, and other analytics capabilities.
The course develops essential SQL analytics skills within the Databricks environment, including writing analytical queries, working with tables and views, filtering and aggregating data, joining multiple datasets, creating calculated measures, and interpreting query results. Participants learn how to use the SQL editor and related Databricks interfaces to transform business questions into meaningful analytical outputs and reusable reporting assets.
A major component of the training focuses on dashboard development. Participants learn how to create datasets, build visualizations, apply filters, organize multi-page dashboards, configure calculated fields, and present information in an interactive format. Databricks AI/BI dashboards support AI-assisted authoring, visualization, cross-filtering, drill-through, custom calculations, and organization-wide sharing, making them suitable for modern self-service analytics.
The course also introduces data modeling and semantic concepts that improve the consistency and reusability of analytics. Learners explore SQL datasets, dashboard calculations, local metric views, dashboard relationships, and governed metrics. These capabilities help analysts structure analytical logic so that measures and relationships can be reused across visualizations and dashboards while supporting consistent business interpretation.
Participants will also learn how to operationalize and share analytical content. The training covers dashboard publishing, permissions, scheduled refreshes, subscriptions, embedding, alerts, and connections to external business intelligence tools. Databricks supports integrations with tools such as Power BI and Tableau, as well as standard JDBC and ODBC connectivity for BI and application scenarios.
By the end of the course, participants will be able to develop complete SQL analytics and dashboarding solutions in Databricks, from querying and modeling data through visualization, interactivity, publishing, and monitoring. Hands-on exercises and a practical capstone project reinforce the skills needed to turn enterprise datasets into reliable, interactive, and decision-supporting analytics assets.
Duration
5 days
Who Should Attend
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Data analysts seeking practical Databricks SQL and dashboarding skills.
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Business intelligence professionals working with modern cloud data platforms.
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BI developers developing interactive analytics and reporting solutions.
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SQL developers transitioning to Databricks SQL and lakehouse-based analytics.
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Reporting specialists responsible for creating dashboards and management reports.
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Data engineers who need to understand the analytics and reporting layer of Databricks.
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Business users who want to develop self-service analytics capabilities using Databricks.
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Database professionals expanding their expertise into cloud data warehousing and analytics.
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Data scientists who need efficient SQL-based exploration and visualization capabilities.
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Analytics managers and technical leads overseeing Databricks reporting initiatives.
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Consultants implementing Databricks SQL analytics and dashboarding solutions for organizations.
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Professionals preparing for Databricks-focused analytics projects or certification-oriented learning.
Course Objectives
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Understand the architecture and core capabilities of Databricks SQL and how SQL warehouses support scalable analytics on lakehouse data.
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Write effective SQL queries in Databricks to filter, aggregate, join, transform, and analyze datasets for meaningful business and operational insights.
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Work confidently with tables, views, schemas, catalogs, and other data objects while applying appropriate approaches for analytical data exploration.
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Build reusable analytical datasets that provide reliable foundations for visualizations, dashboards, metrics, reports, and downstream business intelligence.
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Create interactive AI/BI dashboards using appropriate visualizations, layouts, filters, calculated fields, and page structures for different audiences.
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Apply data modeling and semantic techniques to define consistent measures, relationships, calculations, and business logic across analytical dashboards.
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Improve SQL query performance by understanding execution behavior, query history, query profiles, warehouse considerations, and practical optimization techniques.
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Configure dashboard sharing, publishing, scheduling, subscriptions, permissions, and other features required to distribute analytics securely and consistently.
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Explore Databricks AI/BI capabilities, including AI-assisted dashboard authoring and conversational analytics features that support more accessible data exploration.
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Design and deliver an end-to-end analytics project that combines SQL querying, data modeling, visualization, dashboard interactivity, publishing, and operational management.
Comprehensive Course Outline
Module 1: Introduction to Databricks SQL Analytics
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Understanding Databricks SQL architecture and its role as a cloud data warehouse built on lakehouse architecture.
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Exploring SQL warehouses, the SQL editor, catalogs, schemas, tables, views, dashboards, alerts, and other core analytics components.
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Understanding how Databricks SQL supports direct analytics on lakehouse data without requiring data to be moved into a separate warehouse.
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Reviewing the end-to-end analytics workflow from data exploration and SQL development through visualization, sharing, automation, and monitoring.
Module 2: SQL Querying Fundamentals in Databricks
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Writing SELECT statements and applying filtering, sorting, grouping, aggregation, aliases, expressions, and conditional logic to analytical datasets.
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Working with SQL functions for dates, strings, numbers, null values, conditional calculations, and common analytical transformations.
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Using joins, subqueries, common table expressions, and set operations to combine and analyze information from multiple business datasets.
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Developing readable and maintainable SQL queries that can be reused as foundations for datasets, visualizations, dashboards, and reporting workflows.
Module 3: Advanced SQL Analytics and Data Exploration
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Applying window functions, ranking, partitioning, running totals, moving calculations, and other advanced analytical SQL techniques.
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Analyzing time-series information using date functions, period comparisons, trends, seasonality, and business reporting intervals.
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Performing cohort, segmentation, variance, contribution, and comparative analysis to answer complex business questions using SQL.
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Using query results and exploratory analysis techniques to identify trends, anomalies, performance changes, and opportunities for deeper investigation.
Module 4: SQL Warehouses and Query Performance
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Understanding SQL warehouse concepts, compute configuration, workload requirements, and the relationship between warehouses and query execution.
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Reviewing query history and query profiles to investigate execution times, resource consumption, bottlenecks, and inefficient analytical queries.
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Applying practical SQL optimization techniques such as reducing unnecessary data processing, improving joins, filtering effectively, and simplifying query logic.
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Understanding performance considerations when building datasets and dashboards that repeatedly execute queries against large analytical workloads.
Module 5: Building Analytical Datasets and Data Models
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Creating dashboard datasets from tables, views, and custom SQL queries to provide structured sources for analytical visualizations.
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Developing calculated fields, measures, and reusable analytical logic to support consistent reporting and meaningful business calculations.
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Understanding local metric views, dashboard relationships, semantic modeling, and approaches for organizing complex analytical relationships.
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Designing analytical models that support multiple visualizations and audiences while reducing duplicated calculations and inconsistent business definitions.
Module 6: Databricks AI/BI Dashboard Development
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Creating AI/BI dashboards and organizing datasets, visualizations, pages, widgets, titles, descriptions, and layouts for effective business reporting.
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Selecting appropriate chart types and visualization techniques for trends, comparisons, distributions, rankings, geographic information, and performance indicators.
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Applying filters, cross-filtering, drill-through, custom calculations, and interactive controls to help dashboard users explore information efficiently.
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Using AI-assisted authoring capabilities to accelerate dashboard creation while reviewing generated outputs for analytical accuracy and business relevance.
Module 7: Dashboard Design, Usability, and Business Storytelling
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Applying dashboard design principles to organize information logically and make important trends, measures, exceptions, and insights easy to identify.
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Designing executive, operational, financial, sales, marketing, and performance dashboards around clearly defined business questions and audiences.
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Using appropriate visual hierarchy, layouts, labels, formatting, filters, and contextual information to improve dashboard readability and usability.
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Evaluating dashboards for accuracy, consistency, accessibility, responsiveness, and the ability to communicate actionable information effectively.
Module 8: Publishing, Sharing, and Dashboard Automation
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Publishing dashboards and configuring appropriate permissions so analytical content can be shared securely with intended users and audiences.
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Scheduling dashboard refreshes and configuring subscriptions so stakeholders can receive updated reports and analytical information automatically.
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Understanding dashboard embedding and account-level sharing options for delivering Databricks analytics to broader organizational and application environments.
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Using automation capabilities such as Lakeflow Jobs and related workflows to support repeatable dashboard refresh and reporting processes.
Module 9: Alerts, BI Integrations, and Conversational Analytics
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Creating and managing alerts that monitor query results and conditions so users can receive notifications when important analytical thresholds are reached.
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Connecting Databricks SQL to external BI platforms and understanding common integration approaches using supported connectors, JDBC, ODBC, and partner tools.
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Exploring integrations with business intelligence platforms such as Power BI and Tableau for organizations that use multiple analytics and visualization environments.
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Understanding AI/BI Genie capabilities and conversational approaches that allow business users to explore governed data using natural-language questions.
Module 10: End-to-End SQL Analytics and Dashboarding Project
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Defining a realistic business analytics requirement and identifying the datasets, metrics, dimensions, calculations, and analytical questions needed to address it.
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Developing optimized Databricks SQL queries and reusable datasets that transform raw or prepared data into meaningful analytical information.
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Building an interactive multi-page AI/BI dashboard with appropriate visualizations, filters, calculated metrics, semantic logic, and user-focused design.
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Publishing and presenting the completed solution while applying performance, governance, sharing, refresh, and maintainability practices to the final analytics asset.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
