Technology and Digital Skills Practitioner

A Technology & Digital Skills Practitioner needs a blend of technical, analytical, communication, and modern digital fluency skills. Below is a structured list of 100 essential skills across key domains.

Core Digital Literacy (1–15)

1. Operating systems navigation (Windows/macOS/Linux basics)

2. File management and cloud storage use

3. Digital communication tools (email, chat, video conferencing)

4. Internet research and advanced search techniques

5. Cyber hygiene basics (passwords, phishing awareness)

6. Basic troubleshooting of devices and apps

7. Keyboard shortcuts and productivity optimization

8. Browser tools and extensions usage

9. Digital note-taking systems (Notion, OneNote, etc.)

10. File formats understanding (PDF, CSV, DOCX, etc.)

11. Installing and updating software safely

12. Digital identity management

13. Online collaboration etiquette

14. Multi-device syncing and workflows

15. Basic data backup and recovery practices

Data & Analytics Skills (16–30)

16. Spreadsheet mastery (Excel/Google Sheets)

17. Data cleaning and preprocessing

18. Basic data visualization (charts, graphs)

19. Understanding datasets and data types

20. Descriptive statistics fundamentals

21. SQL querying basics

22. Data interpretation and insight generation

23. Dashboard tools (Power BI/Tableau basics)

24. KPI definition and tracking

25. Data storytelling

26. Spreadsheet formulas (VLOOKUP, IF, INDEX/MATCH)

27. Pivot tables usage

28. Basic Python for data analysis

29. Data ethics and privacy awareness

30. Trend identification from data

Programming & Automation (31–45)

31. Basic Python programming

32. JavaScript fundamentals

33. HTML structure understanding

34. CSS styling basics

35. Git version control basics

36. Command line interface usage

37. API understanding (REST basics)

38. Automation using scripts

39. Debugging code

40. Workflow automation tools (Zapier/Make)

41. Basic software development lifecycle understanding

42. Writing simple functions and loops

43. JSON and data formatting

44. Testing and validation basics

45. Low-code/no-code platforms usage

Digital Tools & Platforms (46–60)

46. CRM systems (Salesforce/HubSpot basics)

47. Content Management Systems (WordPress)

48. Social media platforms management

49. Email marketing tools (Mailchimp, etc.)

50. Project management tools (Trello/Asana/Jira)

51. Video conferencing tools mastery

52. File collaboration tools (Google Drive/SharePoint)

53. Cloud computing basics (AWS/Azure/GCP awareness)

54. SaaS tool navigation

55. Digital scheduling tools

56. Webinar hosting platforms

57. Online survey tools (Google Forms/Typeform)

58. Digital workflow design

59. Tool integration across platforms

60. Subscription SaaS management

Cybersecurity & Digital Safety (61–70)

61. Cybersecurity fundamentals

62. Password management tools

63. Two-factor authentication setup

64. Data privacy principles (GDPR awareness)

65. Secure browsing habits

66. Malware and virus awareness

67. Social engineering awareness

68. Secure file sharing practices

69. Risk identification in digital systems

70. Incident reporting basics

AI, Automation & Emerging Tech (71–80)

71. AI tool usage (ChatGPT, copilot, etc.)

72. Prompt engineering basics

73. Machine learning awareness (conceptual)

74. Automation thinking mindset

75. Generative AI applications in work

76. Chatbot usage and configuration

77. Workflow AI integration

78. Digital assistants usage

79. Awareness of emerging tech trends

80. Ethical AI usage

Business & Workplace Skills (81–90)

81. Digital project management

82. Stakeholder communication

83. Requirements gathering

84. Business process mapping

85. Agile fundamentals

86. Time management in digital environments

87. Remote work collaboration

88. Reporting and documentation

89. Presentation skills (PowerPoint/Google Slides)

90. Problem-solving in tech environments

Advanced & Meta Skills (91–100)

91. Systems thinking

92. Critical thinking and analysis

93. Learning agility (fast upskilling)

94. Adaptability to new tools

95. Digital creativity and innovation

96. UX/UI awareness

97. Customer-centric thinking

98. Technical communication (explaining simply)

99. Cross-functional collaboration

100. Continuous self-learning mindset

The Business Intelligence (BI) landscape is evolving rapidly with AI, automation, cloud analytics, and self-service reporting. Below are the latest tools, technologies, and must-have skills for a modern BI professional.

Modern BI Platforms

1. Microsoft Power BI

2. Tableau

3. Qlik Sense

4. Looker

5. Looker Studio

6. Amazon QuickSight

7. SAP Analytics Cloud

8. IBM Cognos Analytics

9. Oracle Analytics Cloud

10. Domo

AI-Powered Analytics

11. AI-assisted dashboard creation

12. Natural language queries (Ask your data)

13. AI-generated insights

14. Predictive analytics

15. Automated anomaly detection

16. Root cause analysis using AI

17. AI forecasting

18. AI-generated executive summaries

19. Conversational BI

20. Generative AI for reporting

Data Visualization Skills

21. Executive dashboard design

22. Storytelling with data

23. KPI design

24. Interactive dashboards

25. Drill-through reports

26. Drill-down analysis

27. Mobile dashboard optimization

28. Custom themes

29. Data visualization best practices

30. User experience (UX) for dashboards

Data Modelling

31. Star schema

32. Snowflake schema

33. Fact tables

34. Dimension tables

35. Data relationships

36. Normalization

37. Denormalization

38. Slowly Changing Dimensions (SCD)

39. Semantic models

40. Tabular modelling

SQL Skills

41. Advanced SQL

42. Window functions

43. Common Table Expressions (CTEs)

44. Stored procedures

45. Query optimization

46. Joins mastery

47. Aggregate functions

48. Index optimization

49. Data cleansing with SQL

50. SQL performance tuning

Power BI Specialist Skills

51. DAX formulas

52. Power Query (M)

53. Dataflows

54. Fabric integration

55. Composite models

56. Incremental refresh

57. Deployment pipelines

58. Paginated reports

59. Calculation groups

60. Row-Level Security (RLS)

Microsoft Fabric & Cloud

61. Microsoft Fabric

62. OneLake

63. Lakehouse architecture

64. Warehouse architecture

65. Real-time Intelligence

66. Data Factory

67. Notebooks

68. Event Streams

69. Mirroring

70. Direct Lake mode

Data Engineering Fundamentals

71. ETL development

72. ELT architecture

73. Data pipelines

74. Data warehousing

75. Data lakes

76. Lakehouse concepts

77. API integration

78. JSON processing

79. CSV automation

80. Data quality management

Programming Skills

81. Python

82. R

83. REST APIs

84. Scripting automation

85. Git version control

86. Notebook development

87. Data transformation

88. Statistical analysis

89. Machine learning basics

90. Prompt engineering for BI

Business Skills

91. Financial reporting

92. Sales analytics

93. Marketing analytics

94. HR analytics

95. Supply chain analytics

96. Business process mapping

97. Requirements gathering

98. Stakeholder management

99. Data governance

100. Data literacy coaching

The Most Valuable Skills in 2026

If you wanted to become a top 5% BI professional today, I'd prioritize these:

• Advanced SQL

• Power BI

• DAX

• Power Query (M)

• Microsoft Fabric

• Python

• AI Prompt Engineering

• Data Storytelling

• Executive Dashboard Design

• Data Modelling

• Azure Data Services

• Cloud Data Warehousing

• ETL/ELT Pipelines

• Git

• Data Governance

Emerging Trends (2026–2028)

These are becoming increasingly important:

• AI agents that build reports automatically

• Natural-language business intelligence

• Conversational dashboards

• Real-time streaming analytics

• Microsoft Fabric as a unified analytics platform

• Lakehouse architecture replacing traditional warehouses

• AI copilots embedded in BI tools

• Semantic layers for enterprise data

• Automated data quality monitoring

• Self-service analytics governed by centralized data models

Professionals who combine business understanding, data engineering, visualization, and AI-assisted analytics are increasingly in demand, as organizations expect BI specialists to move beyond reporting into strategic decision support.

Here are practical "How To" Power BI skills that take someone from beginner to advanced.

Getting Started

1. How to install Power BI Desktop.

2. How to connect to Excel.

3. How to connect to SQL Server.

4. How to connect to SharePoint.

5. How to connect to Azure SQL Database.

6. How to connect to APIs.

7. How to import CSV files.

8. How to choose between Import and DirectQuery.

9. How to publish reports to Power BI Service.

10. How to refresh a dataset.

Importing & Cleaning Data

11. How to use Power Query.

12. How to remove duplicate rows.

13. How to remove null values.

14. How to split columns.

15. How to merge columns.

16. How to append queries.

17. How to merge queries.

18. How to change data types.

19. How to pivot columns.

20. How to unpivot columns.

Data Modelling

21. How to create relationships.

22. How to create a star schema.

23. How to create dimension tables.

24. How to create fact tables.

25. How to create calculated tables.

26. How to create calculated columns.

27. How to create measures.

28. How to manage many-to-many relationships.

29. How to use inactive relationships.

30. How to optimise the data model.

DAX Basics

31. How to write your first DAX formula.

32. How to use SUM().

33. How to use AVERAGE().

34. How to use COUNTROWS().

35. How to use DISTINCTCOUNT().

36. How to use IF().

37. How to use SWITCH().

38. How to use DIVIDE().

39. How to use RELATED().

40. How to use LOOKUPVALUE().

Advanced DAX

41. How to calculate Year-to-Date sales.

42. How to calculate Month-to-Date sales.

43. How to calculate Quarter-to-Date.

44. How to calculate rolling averages.

45. How to calculate moving totals.

46. How to compare current vs previous year.

47. How to rank products.

48. How to calculate percentages of total.

49. How to use CALCULATE().

50. How to use FILTER().

Visualisations

51. How to build a dashboard.

52. How to create a KPI card.

53. How to build a bar chart.

54. How to build a line chart.

55. How to build a pie chart.

56. How to build a waterfall chart.

57. How to build a treemap.

58. How to build a gauge.

59. How to build a scatter chart.

60. How to build a matrix.

Interactive Reports

61. How to create slicers.

62. How to sync slicers.

63. How to create drill-down reports.

64. How to create drill-through pages.

65. How to use bookmarks.

66. How to create navigation buttons.

67. How to use tooltips.

68. How to create report page tooltips.

69. How to use field parameters.

70. How to create dynamic titles.

Power BI Service

71. How to publish reports.

72. How to schedule refreshes.

73. How to share dashboards.

74. How to manage workspaces.

75. How to create Apps.

76. How to manage permissions.

77. How to configure Row-Level Security.

78. How to monitor usage metrics.

79. How to create subscriptions.

80. How to export reports.

Microsoft Fabric Integration

81. How to connect to Microsoft Fabric.

82. How to use OneLake.

83. How to use Lakehouse data.

84. How to connect to a Warehouse.

85. How to use Direct Lake.

86. How to build Real-Time dashboards.

87. How to use Dataflows Gen2.

88. How to connect to Notebooks.

89. How to automate pipelines.

90. How to use Fabric Copilot.

Advanced BI Skills

91. How to optimise report performance.

92. How to reduce report loading time.

93. How to build executive dashboards.

94. How to design mobile reports.

95. How to implement governance.

96. How to document a Power BI solution.

97. How to automate report delivery.

98. How to use AI visuals.

99. How to build a complete business intelligence solution.

100. How to tell compelling business stories with data.

If you're aiming to become a senior Power BI developer, master these first:

• Power Query (M)

• DAX

• Data Modelling (Star Schema)

• SQL

• Dashboard Design

• Performance Optimisation

• Row-Level Security (RLS)

• Microsoft Fabric

• AI Copilot features

• Data Storytelling

These 100 "how-to" topics form a strong roadmap from beginner to expert-level Power BI proficiency.

Here are practical Tableau "How To" skills that progress from beginner to advanced and reflect what employers look for in BI and analytics professionals.

Getting Started

1. How to install Tableau Desktop.

2. How to connect to Excel.

3. How to connect to SQL Server.

4. How to connect to PostgreSQL.

5. How to connect to MySQL.

6. How to connect to Oracle databases.

7. How to connect to Google Sheets.

8. How to connect to cloud data sources.

9. How to create a new workbook.

10. How to save and publish a workbook.

Connecting & Preparing Data

11. How to create a live connection.

12. How to create an extract.

13. How to clean imported data.

14. How to rename fields.

15. How to change data types.

16. How to split fields.

17. How to pivot data.

18. How to union tables.

19. How to join tables.

20. How to create relationships between tables.

Data Modelling

21. How to build a logical data model.

22. How to build a physical data model.

23. How to use relationships instead of joins.

24. How to optimise data models.

25. How to create calculated fields.

26. How to create aliases.

27. How to create groups.

28. How to create hierarchies.

29. How to create sets.

30. How to create parameters.

Calculated Fields

31. How to create basic calculations.

32. How to use IF statements.

33. How to use CASE statements.

34. How to use DATE functions.

35. How to use STRING functions.

36. How to use NUMBER functions.

37. How to create Boolean calculations.

38. How to create conditional calculations.

39. How to create custom metrics.

40. How to combine multiple calculations.

Level of Detail (LOD) Expressions

41. How to use FIXED LOD.

42. How to use INCLUDE LOD.

43. How to use EXCLUDE LOD.

44. How to calculate customer lifetime value.

45. How to calculate average sales per customer.

46. How to remove duplicate counting.

47. How to aggregate correctly.

48. How to solve granularity issues.

49. How to compare detailed and summary data.

50. How to optimise LOD calculations.

Charts & Visualisations

51. How to create bar charts.

52. How to create line charts.

53. How to create area charts.

54. How to create pie charts.

55. How to create treemaps.

56. How to create heat maps.

57. How to create scatter plots.

58. How to create box plots.

59. How to create histograms.

60. How to create bullet graphs.

Geographic Analytics

61. How to create maps.

62. How to use geographic roles.

63. How to build filled maps.

64. How to create symbol maps.

65. How to create density maps.

66. How to map custom locations.

67. How to add latitude and longitude.

68. How to create territory maps.

69. How to build regional dashboards.

70. How to customise map layers.

Dashboards

71. How to build a dashboard.

72. How to add dashboard actions.

73. How to use filters.

74. How to create parameter actions.

75. How to create highlight actions.

76. How to add navigation buttons.

77. How to optimise dashboard layout.

78. How to make dashboards mobile-friendly.

79. How to create interactive dashboards.

80. How to design executive dashboards.

Tableau Server & Cloud

81. How to publish to Tableau Server.

82. How to publish to Tableau Cloud.

83. How to schedule extract refreshes.

84. How to manage permissions.

85. How to manage projects.

86. How to create subscriptions.

87. How to share dashboards securely.

88. How to monitor server performance.

89. How to certify data sources.

90. How to manage user access.

Advanced Tableau Skills

91. How to optimise workbook performance.

92. How to reduce dashboard load times.

93. How to use Tableau Prep.

94. How to automate data preparation.

95. How to integrate Python with Tableau.

96. How to integrate R with Tableau.

97. How to embed Tableau dashboards into websites.

98. How to implement row-level security.

99. How to build enterprise BI solutions.

100. How to tell compelling business stories with Tableau.

The Top 20 Skills Every Tableau Developer Should Master

• Data connections

• Data modelling

• Relationships and joins

• Tableau Prep

• Calculated fields

• Parameters

• Sets

• Groups

• Hierarchies

• Level of Detail (LOD) expressions

• Table calculations

• Dashboard design

• Interactive dashboards

• Mapping and geospatial analytics

• Performance optimisation

• Tableau Server administration

• Tableau Cloud publishing

• Row-level security

• SQL for analytics

• Data storytelling

Mastering these skills will prepare you for roles such as Tableau Developer, BI Analyst, Analytics Consultant, Data Visualization Specialist, Business Intelligence Engineer, and Senior Analytics Consultant.

Here are practical "How To" Qlik Sense skills, progressing from beginner to advanced, aligned with what employers seek in modern Business Intelligence professionals.

Getting Started

1. How to install Qlik Sense Desktop.

2. How to create your first app.

3. How to connect to Excel.

4. How to connect to CSV files.

5. How to connect to SQL Server.

6. How to connect to Oracle databases.

7. How to connect to PostgreSQL.

8. How to connect to cloud databases.

9. How to navigate the Qlik Sense Hub.

10. How to publish an app.

Loading Data

11. How to use the Data Manager.

12. How to use the Data Load Editor.

13. How to load multiple files.

14. How to concatenate tables.

15. How to join tables.

16. How to keep tables separate.

17. How to rename fields.

18. How to change data types.

19. How to filter records during load.

20. How to reload data.

Scripting

21. How to write a Qlik load script.

22. How to use Resident Load.

23. How to use Preceding Load.

24. How to create variables.

25. How to use LET and SET.

26. How to create calculated fields.

27. How to use IF statements.

28. How to use mapping tables.

29. How to use ApplyMap().

30. How to debug a load script.

Data Modelling

31. How to build a star schema.

32. How to avoid synthetic keys.

33. How to remove circular references.

34. How to use link tables.

35. How to build calendar tables.

36. How to create master dimensions.

37. How to create master measures.

38. How to create master items.

39. How to optimise the data model.

40. How to troubleshoot associations.

Expressions

41. How to write expressions.

42. How to use Sum().

43. How to use Avg().

44. How to use Count().

45. How to use Count Distinct().

46. How to use Aggr().

47. How to use Only().

48. How to use Above().

49. How to use Below().

50. How to create conditional expressions.

Set Analysis

51. How to write Set Analysis expressions.

52. How to compare years.

53. How to calculate Year-to-Date values.

54. How to calculate Month-to-Date values.

55. How to calculate Quarter-to-Date values.

56. How to compare current vs previous year.

57. How to ignore selections.

58. How to create dynamic filters.

59. How to create rolling 12-month calculations.

60. How to optimise Set Analysis.

Visualisations

61. How to build a KPI object.

62. How to create bar charts.

63. How to create line charts.

64. How to create combo charts.

65. How to create pie charts.

66. How to create scatter plots.

67. How to create treemaps.

68. How to create pivot tables.

69. How to create maps.

70. How to create gauges.

Dashboards

71. How to create sheets.

72. How to build executive dashboards.

73. How to add filters.

74. How to create bookmarks.

75. How to use alternate states.

76. How to create drill-down groups.

77. How to add custom themes.

78. How to make dashboards responsive.

79. How to create storytelling presentations.

80. How to optimise dashboard performance.

Qlik Cloud & Enterprise

81. How to publish apps to Qlik Cloud.

82. How to share dashboards securely.

83. How to schedule data reloads.

84. How to automate refreshes.

85. How to create spaces.

86. How to manage permissions.

87. How to use Qlik AutoML.

88. How to use Insight Advisor.

89. How to monitor app usage.

90. How to administer Qlik Enterprise.

Advanced Skills

91. How to optimise app performance.

92. How to reduce memory usage.

93. How to create reusable load scripts.

94. How to integrate REST APIs.

95. How to connect to web services.

96. How to implement row-level security.

97. How to use section access.

98. How to build enterprise BI solutions.

99. How to automate data pipelines.

100. How to tell compelling business stories with Qlik Sense.

The Top 20 Skills Every Qlik Sense Developer Should Master

• Data Load Editor

• Qlik scripting

• Set Analysis

• Data modelling

• Star schema design

• Master Items

• Variables

• Resident Loads

• ApplyMap()

• Calendar tables

• Synthetic key resolution

• Section Access (security)

• Dashboard design

• Performance optimisation

• Incremental data loading

• REST API integration

• Qlik Cloud administration

• Insight Advisor (AI-assisted analytics)

• SQL for data extraction

• Data storytelling

Mastering these skills equips you for roles such as Qlik Sense Developer, Business Intelligence Developer, BI Consultant, Data Analyst, Analytics Engineer, and Enterprise BI Architect, particularly in organizations that rely on associative analytics and self-service business intelligence.

Here are practical “How To” Looker skills covering beginner to advanced capabilities in modern BI and analytics.

Getting Started

1. How to access Looker.

2. How to log into Looker via Google Cloud.

3. How to navigate the Looker interface.

4. How to explore existing dashboards.

5. How to view Looks (saved queries).

6. How to understand Explores.

7. How to switch between projects.

8. How to search dashboards.

9. How to set user preferences.

10. How to understand Looker roles and permissions.

Exploring Data (Explores)

11. How to use an Explore.

12. How to select fields in Explore.

13. How to apply filters in Explore.

14. How to group data by dimensions.

15. How to aggregate measures.

16. How to sort results.

17. How to limit result rows.

18. How to drill into data.

19. How to pivot data.

20. How to save an Explore as a Look.

Looks (Saved Queries)

21. How to create a Look.

22. How to edit a Look.

23. How to schedule a Look.

24. How to download Look results.

25. How to share a Look.

26. How to embed a Look.

27. How to duplicate a Look.

28. How to organize Looks into folders.

29. How to set Look permissions.

30. How to delete a Look.

Dashboards

31. How to create a dashboard.

32. How to add tiles to dashboards.

33. How to connect Explores to dashboards.

34. How to add filters to dashboards.

35. How to create dashboard links.

36. How to schedule dashboard delivery.

37. How to build executive dashboards.

38. How to customize dashboard layout.

39. How to embed dashboards.

40. How to share dashboards securely.

LookML Basics (Core Development)

41. How to define a LookML project.

42. How to create a view file.

43. How to define a model file.

44. How to connect Looker to a database.

45. How to define dimensions.

46. How to define measures.

47. How to create derived tables.

48. How to use SQL in LookML.

49. How to validate LookML code.

50. How to deploy LookML changes.

Advanced LookML

51. How to create joins in LookML.

52. How to define relationships between views.

53. How to build persistent derived tables (PDTs).

54. How to optimize SQL queries.

55. How to create complex measures.

56. How to use templated filters.

57. How to use parameterized fields.

58. How to create conditional logic in LookML.

59. How to manage multiple environments.

60. How to version control LookML with Git.

Data Modelling

61. How to design a semantic layer.

62. How to build a star schema in Looker.

63. How to optimize joins for performance.

64. How to avoid fan-out issues.

65. How to manage many-to-many relationships.

66. How to structure reusable views.

67. How to define aggregate awareness.

68. How to handle null values.

69. How to normalize data sources.

70. How to document data models.

Visualization & Analytics

71. How to build bar charts.

72. How to build line charts.

73. How to build scatter plots.

74. How to build pivot tables.

75. How to build heatmaps.

76. How to create KPI tiles.

77. How to create funnel charts.

78. How to use table calculations.

79. How to build cohort analysis.

80. How to create trend analysis dashboards.

Security & Governance

81. How to set user roles.

82. How to configure permissions.

83. How to implement row-level security.

84. How to restrict data access by user.

85. How to audit user activity.

86. How to manage content folders.

87. How to enforce data governance policies.

88. How to certify data models.

89. How to manage data access layers.

90. How to secure embedded analytics.

Integration & Automation

91. How to connect Looker to BigQuery.

92. How to integrate Looker with APIs.

93. How to embed Looker in applications.

94. How to automate data refreshes.

95. How to schedule data deliveries.

96. How to integrate Looker with Slack.

97. How to export data to Google Sheets.

98. How to use Looker webhooks.

99. How to monitor query performance.

100. How to build scalable enterprise BI solutions.

Top Skills to Master in Looker (High Value)

• LookML development

• Semantic layer design

• SQL optimization

• Data modelling (star schema)

• Dashboard design

• Explores & self-service analytics

• Git version control

• Row-level security

• BigQuery integration

• Performance tuning

• Embedded analytics

• API automation

• Business storytelling

Here are practical “How To” Looker Studio skills (formerly Google Data Studio), covering beginner → advanced BI reporting, dashboards, and data storytelling.

Getting Started

1. How to access Looker Studio.

2. How to create your first report.

3. How to connect Google Sheets.

4. How to connect Google Analytics.

5. How to connect BigQuery.

6. How to connect CSV files.

7. How to connect Google Ads.

8. How to navigate the report editor.

9. How to switch between edit and view mode.

10. How to share a report.

Data Connections

11. How to add a data source.

12. How to edit a data source.

13. How to blend multiple data sources.

14. How to refresh data connections.

15. How to replace a data source.

16. How to manage data credentials.

17. How to connect to SQL databases.

18. How to connect to third-party connectors.

19. How to use community connectors.

20. How to troubleshoot broken data sources.

Data Preparation

21. How to rename fields.

22. How to change data types.

23. How to create calculated fields.

24. How to use CASE statements.

25. How to create custom metrics.

26. How to create date fields.

27. How to filter data at source level.

28. How to aggregate metrics.

29. How to handle null values.

30. How to create parameters.

Report Building Basics

31. How to add a chart.

32. How to add a table.

33. How to add scorecards.

34. How to add time series charts.

35. How to add pie charts.

36. How to add bar charts.

37. How to add geo maps.

38. How to add scatter plots.

39. How to add pivot tables.

40. How to add text boxes.

Dashboard Design

41. How to create a dashboard layout.

42. How to use theme settings.

43. How to format colors and fonts.

44. How to align components.

45. How to use grids and guides.

46. How to create multi-page reports.

47. How to design executive dashboards.

48. How to create mobile-friendly layouts.

49. How to use containers.

50. How to create visual hierarchy.

Filters & Controls

51. How to add date range filters.

52. How to add dropdown filters.

53. How to add search filters.

54. How to add slider controls.

55. How to apply filter controls globally.

56. How to create report-level filters.

57. How to create chart-level filters.

58. How to sync filters across pages.

59. How to reset filters.

60. How to use advanced filter logic.

Calculations & Metrics

61. How to write calculated fields.

62. How to calculate conversion rate.

63. How to calculate ROI.

64. How to calculate CTR.

65. How to calculate growth rate.

66. How to calculate year-over-year change.

67. How to create running totals.

68. How to calculate averages.

69. How to create conditional metrics.

70. How to use regex formulas.

Visualization Techniques

71. How to create trend analysis charts.

72. How to build funnel visualizations.

73. How to create cohort charts.

74. How to build KPI dashboards.

75. How to visualize geographic data.

76. How to compare time periods.

77. How to show ranking charts.

78. How to build engagement dashboards.

79. How to highlight anomalies.

80. How to create storytelling dashboards.

Sharing & Collaboration

81. How to share reports with users.

82. How to set viewer vs editor permissions.

83. How to publish reports.

84. How to embed reports in websites.

85. How to export reports as PDF.

86. How to schedule email delivery.

87. How to collaborate in real-time.

88. How to comment on reports.

89. How to manage access control.

90. How to duplicate reports safely.

Advanced Looker Studio Skills

91. How to use community visualizations.

92. How to use BigQuery SQL custom queries.

93. How to optimize report performance.

94. How to reduce data loading time.

95. How to handle large datasets.

96. How to use blended data performance tuning.

97. How to build enterprise dashboards.

98. How to integrate Google Sheets automation.

99. How to use API-driven reporting.

100. How to build automated business intelligence systems.

High-Value Skills to Master (2026 BI Market)

• BigQuery integration

• Data blending strategy

• Calculated fields mastery

• Dashboard UX design

• Performance optimization

• Marketing analytics (CTR, ROI, CAC)

• SQL fundamentals

• Google ecosystem integration

• Data storytelling

• Automation & scheduling

• Funnel & cohort analysis

• KPI design

Here are practical “How To” Amazon QuickSight skills, covering beginner to advanced BI, cloud analytics, and AWS-native reporting.

Getting Started

1. How to access Amazon QuickSight.

2. How to sign up for QuickSight on AWS.

3. How to create your first dataset.

4. How to connect to AWS S3.

5. How to connect to Amazon RDS.

6. How to connect to Amazon Redshift.

7. How to connect to Athena.

8. How to upload a file dataset.

9. How to navigate the QuickSight console.

10. How to create your first analysis.

Data Sources & Connections

11. How to connect to SQL databases.

12. How to connect to cloud data warehouses.

13. How to import CSV files.

14. How to use SPICE in QuickSight.

15. How to manage SPICE capacity.

16. How to use direct query mode.

17. How to refresh datasets.

18. How to schedule data refreshes.

19. How to manage dataset permissions.

20. How to troubleshoot data connection issues.

Data Preparation

21. How to clean data in QuickSight Prep.

22. How to rename fields.

23. How to change data types.

24. How to create calculated fields.

25. How to filter datasets.

26. How to join datasets.

27. How to append datasets.

28. How to aggregate data.

29. How to handle null values.

30. How to build curated datasets.

Calculations

31. How to write calculated fields.

32. How to use ifelse() functions.

33. How to use sum() and avg().

34. How to calculate profit margins.

35. How to calculate growth rates.

36. How to calculate year-over-year change.

37. How to create running totals.

38. How to use level-aware calculations.

39. How to create conditional metrics.

40. How to create custom KPIs.

Visualizations

41. How to create bar charts.

42. How to create line charts.

43. How to create combo charts.

44. How to create pie charts.

45. How to create donut charts.

46. How to create scatter plots.

47. How to create heat maps.

48. How to create pivot tables.

49. How to create KPI visuals.

50. How to create funnel charts.

Dashboards & Analyses

51. How to create an analysis.

52. How to build dashboards.

53. How to add multiple sheets.

54. How to link visuals.

55. How to create drill-downs.

56. How to create drill-through actions.

57. How to add filters.

58. How to sync filters.

59. How to use parameters.

60. How to design executive dashboards.

Interactivity

61. How to add filter controls.

62. How to add date range controls.

63. How to use dropdown filters.

64. How to create custom actions.

65. How to highlight data points.

66. How to enable cross-filtering.

67. How to create dynamic titles.

68. How to build responsive dashboards.

69. How to use toggle views.

70. How to add tooltips.

Advanced Visual Analytics

71. How to perform cohort analysis.

72. How to build sales performance dashboards.

73. How to perform trend analysis.

74. How to identify anomalies.

75. How to build forecasting visuals.

76. How to segment customers.

77. How to analyse churn.

78. How to calculate LTV (lifetime value).

79. How to perform funnel analysis.

80. How to build operational dashboards.

Security & Governance

81. How to set up IAM roles.

82. How to manage QuickSight permissions.

83. How to implement row-level security.

84. How to create user groups.

85. How to share dashboards securely.

86. How to manage datasets access.

87. How to audit usage.

88. How to control SPICE access.

89. How to encrypt data sources.

90. How to comply with AWS security standards.

Enterprise & AWS Integration

91. How to integrate with AWS Glue.

92. How to connect to AWS Lambda.

93. How to use Athena SQL queries.

94. How to connect to Redshift clusters.

95. How to embed QuickSight dashboards.

96. How to use APIs for automation.

97. How to schedule report delivery.

98. How to monitor performance.

99. How to scale QuickSight usage.

100. How to build enterprise BI solutions on AWS.

High-Value Skills in QuickSight (2026)

• SPICE in-memory optimization

• AWS data warehouse integration (Redshift, Athena)

• IAM security management

• Calculated fields mastery

• Dashboard storytelling

• Serverless BI architecture

• Embedded analytics

• Data governance in AWS

• SQL (Athena/Redshift)

• Performance optimization

• Cloud cost management

• Automated reporting pipelines

Here is a curated list of 100 UK companies hiring or actively using BI reporting (Power BI, Tableau, Qlik, Looker, AWS QuickSight, etc.) based on current UK job market patterns, enterprise BI stacks, and live job postings.

I’ve grouped them so you can actually use this for targeting.

 UK Companies Hiring BI / Reporting Talent

 Banking & Financial Services (highest BI demand)

1. Lloyds Banking Group

2. Barclays

3. HSBC

4. NatWest Group

5. Santander UK

6. Standard Chartered

7. Nationwide Building Society

8. Virgin Money

9. Metro Bank

10. Close Brothers

 Insurance & Risk Analytics

11. Aviva

12. AXA UK

13. Direct Line Group

14. Admiral Group

15. Legal & General

16. Zurich UK

17. Hiscox

18. RSA Insurance

19. Bupa Global

20. Markel UK

 Retail & E-commerce

21. Tesco

22. Sainsbury’s

23. ASDA

24. Morrisons

25. Marks & Spencer

26. John Lewis Partnership

27. Ocado Group

28. Amazon UK

29. Argos (Sainsbury’s Group)

30. Next PLC

 Manufacturing & Engineering

31. Rolls-Royce

32. BAE Systems

33. Jaguar Land Rover

34. Bentley Motors

35. Aston Martin

36. Siemens UK

37. GE Aerospace UK

38. British Steel

39. Schneider Electric UK

40. Caterpillar UK

 Healthcare & Pharma

41. NHS Digital

42. NHS England

43. AstraZeneca UK

44. GSK (GlaxoSmithKline)

45. Pfizer UK

46. Roche UK

47. Johnson & Johnson UK

48. Bayer UK

49. Boots UK

50. Bupa

 Consulting & Big 4 (huge BI hiring)

51. Deloitte UK

52. PwC UK

53. EY UK

54. KPMG UK

55. Accenture UK

56. Capgemini

57. Cognizant UK

58. Infosys UK

59. Wipro UK

60. Tata Consultancy Services (TCS UK)

 Tech, Data & SaaS Companies

61. Google UK

62. Microsoft UK

63. Amazon Web Services UK

64. Meta UK

65. Salesforce UK

66. Oracle UK

67. Snowflake UK

68. Databricks UK

69. Adobe UK

70. IBM UK

 Transport, Logistics & Travel

71. Transport for London (TfL)

72. Network Rail

73. British Airways

74. EasyJet

75. Ryanair UK

76. Heathrow Airport

77. Gatwick Airport

78. DHL UK

79. Royal Mail

80. Uber UK

 Government & Public Sector

81. UK Home Office

82. HMRC

83. Ministry of Justice

84. Department for Work and Pensions (DWP)

85. UK Ministry of Defence

86. Office for National Statistics (ONS)

87. NHS Business Services Authority

88. UK Parliament Digital Service

89. Local Government Digital Services

90. Cabinet Office

 Telecoms, Media & Utilities

91. BT Group

92. Vodafone UK

93. Sky (Comcast)

94. ITV

95. BBC

96. Channel 4

97. Centrica (British Gas)

98. National Grid

99. Scottish Power

100. SSE PLC

 What this tells you (important insight)

Across all 100 companies:

Most common BI stack in UK jobs:

• Microsoft Power BI (dominant)

• SQL (mandatory everywhere)

• Azure / Microsoft Fabric (fast-growing)

• Tableau (still strong in consulting & analytics teams)

• Qlik (niche but present in legacy enterprises)

• Looker (growing in tech + SaaS)

• AWS QuickSight (cloud-native companies)

 If your goal is to get hired fast in BI (UK market reality)

Focus on:

• Power BI (must-have)

• SQL (non-negotiable)

• Data modelling (star schema)

• DAX (for senior roles)

• Excel (still used everywhere)

• Basic Python (bonus edge)

• Dashboard storytelling (what separates juniors from hires)