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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.
Operating systems navigation (Windows/macOS/Linux basics)
File management and cloud storage use
Digital communication tools (email, chat, video conferencing)
Internet research and advanced search techniques
Cyber hygiene basics (passwords, phishing awareness)
Basic troubleshooting of devices and apps
Keyboard shortcuts and productivity optimization
Browser tools and extensions usage
Digital note-taking systems (Notion, OneNote, etc.)
File formats understanding (PDF, CSV, DOCX, etc.)
Installing and updating software safely
Digital identity management
Online collaboration etiquette
Multi-device syncing and workflows
Basic data backup and recovery practices
Spreadsheet mastery (Excel/Google Sheets)
Data cleaning and preprocessing
Basic data visualization (charts, graphs)
Understanding datasets and data types
Descriptive statistics fundamentals
SQL querying basics
Data interpretation and insight generation
Dashboard tools (Power BI/Tableau basics)
KPI definition and tracking
Data storytelling
Spreadsheet formulas (VLOOKUP, IF, INDEX/MATCH)
Pivot tables usage
Basic Python for data analysis
Data ethics and privacy awareness
Trend identification from data
Basic Python programming
JavaScript fundamentals
HTML structure understanding
CSS styling basics
Git version control basics
Command line interface usage
API understanding (REST basics)
Automation using scripts
Debugging code
Workflow automation tools (Zapier/Make)
Basic software development lifecycle understanding
Writing simple functions and loops
JSON and data formatting
Testing and validation basics
Low-code/no-code platforms usage
CRM systems (Salesforce/HubSpot basics)
Content Management Systems (WordPress)
Social media platforms management
Email marketing tools (Mailchimp, etc.)
Project management tools (Trello/Asana/Jira)
Video conferencing tools mastery
File collaboration tools (Google Drive/SharePoint)
Cloud computing basics (AWS/Azure/GCP awareness)
SaaS tool navigation
Digital scheduling tools
Webinar hosting platforms
Online survey tools (Google Forms/Typeform)
Digital workflow design
Tool integration across platforms
Subscription SaaS management
Cybersecurity fundamentals
Password management tools
Two-factor authentication setup
Data privacy principles (GDPR awareness)
Secure browsing habits
Malware and virus awareness
Social engineering awareness
Secure file sharing practices
Risk identification in digital systems
Incident reporting basics
AI tool usage (ChatGPT, copilot, etc.)
Prompt engineering basics
Machine learning awareness (conceptual)
Automation thinking mindset
Generative AI applications in work
Chatbot usage and configuration
Workflow AI integration
Digital assistants usage
Awareness of emerging tech trends
Ethical AI usage
Digital project management
Stakeholder communication
Requirements gathering
Business process mapping
Agile fundamentals
Time management in digital environments
Remote work collaboration
Reporting and documentation
Presentation skills (PowerPoint/Google Slides)
Problem-solving in tech environments
Systems thinking
Critical thinking and analysis
Learning agility (fast upskilling)
Adaptability to new tools
Digital creativity and innovation
UX/UI awareness
Customer-centric thinking
Technical communication (explaining simply)
Cross-functional collaboration
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.
Microsoft Power BI
Tableau
Qlik Sense
Looker
Looker Studio
Amazon QuickSight
SAP Analytics Cloud
IBM Cognos Analytics
Oracle Analytics Cloud
Domo
AI-assisted dashboard creation
Natural language queries (Ask your data)
AI-generated insights
Predictive analytics
Automated anomaly detection
Root cause analysis using AI
AI forecasting
AI-generated executive summaries
Conversational BI
Generative AI for reporting
Executive dashboard design
Storytelling with data
KPI design
Interactive dashboards
Drill-through reports
Drill-down analysis
Mobile dashboard optimization
Custom themes
Data visualization best practices
User experience (UX) for dashboards
Star schema
Snowflake schema
Fact tables
Dimension tables
Data relationships
Normalization
Denormalization
Slowly Changing Dimensions (SCD)
Semantic models
Tabular modelling
Advanced SQL
Window functions
Common Table Expressions (CTEs)
Stored procedures
Query optimization
Joins mastery
Aggregate functions
Index optimization
Data cleansing with SQL
SQL performance tuning
DAX formulas
Power Query (M)
Dataflows
Fabric integration
Composite models
Incremental refresh
Deployment pipelines
Paginated reports
Calculation groups
Row-Level Security (RLS)
Microsoft Fabric
OneLake
Lakehouse architecture
Warehouse architecture
Real-time Intelligence
Data Factory
Notebooks
Event Streams
Mirroring
Direct Lake mode
ETL development
ELT architecture
Data pipelines
Data warehousing
Data lakes
Lakehouse concepts
API integration
JSON processing
CSV automation
Data quality management
Python
R
REST APIs
Scripting automation
Git version control
Notebook development
Data transformation
Statistical analysis
Machine learning basics
Prompt engineering for BI
Financial reporting
Sales analytics
Marketing analytics
HR analytics
Supply chain analytics
Business process mapping
Requirements gathering
Stakeholder management
Data governance
Data literacy coaching
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
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.
How to install Power BI Desktop.
How to connect to Excel.
How to connect to SQL Server.
How to connect to SharePoint.
How to connect to Azure SQL Database.
How to connect to APIs.
How to import CSV files.
How to choose between Import and DirectQuery.
How to publish reports to Power BI Service.
How to refresh a dataset.
How to use Power Query.
How to remove duplicate rows.
How to remove null values.
How to split columns.
How to merge columns.
How to append queries.
How to merge queries.
How to change data types.
How to pivot columns.
How to unpivot columns.
How to create relationships.
How to create a star schema.
How to create dimension tables.
How to create fact tables.
How to create calculated tables.
How to create calculated columns.
How to create measures.
How to manage many-to-many relationships.
How to use inactive relationships.
How to optimise the data model.
How to write your first DAX formula.
How to use SUM().
How to use AVERAGE().
How to use COUNTROWS().
How to use DISTINCTCOUNT().
How to use IF().
How to use SWITCH().
How to use DIVIDE().
How to use RELATED().
How to use LOOKUPVALUE().
How to calculate Year-to-Date sales.
How to calculate Month-to-Date sales.
How to calculate Quarter-to-Date.
How to calculate rolling averages.
How to calculate moving totals.
How to compare current vs previous year.
How to rank products.
How to calculate percentages of total.
How to use CALCULATE().
How to use FILTER().
How to build a dashboard.
How to create a KPI card.
How to build a bar chart.
How to build a line chart.
How to build a pie chart.
How to build a waterfall chart.
How to build a treemap.
How to build a gauge.
How to build a scatter chart.
How to build a matrix.
How to create slicers.
How to sync slicers.
How to create drill-down reports.
How to create drill-through pages.
How to use bookmarks.
How to create navigation buttons.
How to use tooltips.
How to create report page tooltips.
How to use field parameters.
How to create dynamic titles.
How to publish reports.
How to schedule refreshes.
How to share dashboards.
How to manage workspaces.
How to create Apps.
How to manage permissions.
How to configure Row-Level Security.
How to monitor usage metrics.
How to create subscriptions.
How to export reports.
How to connect to Microsoft Fabric.
How to use OneLake.
How to use Lakehouse data.
How to connect to a Warehouse.
How to use Direct Lake.
How to build Real-Time dashboards.
How to use Dataflows Gen2.
How to connect to Notebooks.
How to automate pipelines.
How to use Fabric Copilot.
How to optimise report performance.
How to reduce report loading time.
How to build executive dashboards.
How to design mobile reports.
How to implement governance.
How to document a Power BI solution.
How to automate report delivery.
How to use AI visuals.
How to build a complete business intelligence solution.
How to tell compelling business stories with data.
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.
How to install Tableau Desktop.
How to connect to Excel.
How to connect to SQL Server.
How to connect to PostgreSQL.
How to connect to MySQL.
How to connect to Oracle databases.
How to connect to Google Sheets.
How to connect to cloud data sources.
How to create a new workbook.
How to save and publish a workbook.
How to create a live connection.
How to create an extract.
How to clean imported data.
How to rename fields.
How to change data types.
How to split fields.
How to pivot data.
How to union tables.
How to join tables.
How to create relationships between tables.
How to build a logical data model.
How to build a physical data model.
How to use relationships instead of joins.
How to optimise data models.
How to create calculated fields.
How to create aliases.
How to create groups.
How to create hierarchies.
How to create sets.
How to create parameters.
How to create basic calculations.
How to use IF statements.
How to use CASE statements.
How to use DATE functions.
How to use STRING functions.
How to use NUMBER functions.
How to create Boolean calculations.
How to create conditional calculations.
How to create custom metrics.
How to combine multiple calculations.
How to use FIXED LOD.
How to use INCLUDE LOD.
How to use EXCLUDE LOD.
How to calculate customer lifetime value.
How to calculate average sales per customer.
How to remove duplicate counting.
How to aggregate correctly.
How to solve granularity issues.
How to compare detailed and summary data.
How to optimise LOD calculations.
How to create bar charts.
How to create line charts.
How to create area charts.
How to create pie charts.
How to create treemaps.
How to create heat maps.
How to create scatter plots.
How to create box plots.
How to create histograms.
How to create bullet graphs.
How to create maps.
How to use geographic roles.
How to build filled maps.
How to create symbol maps.
How to create density maps.
How to map custom locations.
How to add latitude and longitude.
How to create territory maps.
How to build regional dashboards.
How to customise map layers.
How to build a dashboard.
How to add dashboard actions.
How to use filters.
How to create parameter actions.
How to create highlight actions.
How to add navigation buttons.
How to optimise dashboard layout.
How to make dashboards mobile-friendly.
How to create interactive dashboards.
How to design executive dashboards.
How to publish to Tableau Server.
How to publish to Tableau Cloud.
How to schedule extract refreshes.
How to manage permissions.
How to manage projects.
How to create subscriptions.
How to share dashboards securely.
How to monitor server performance.
How to certify data sources.
How to manage user access.
How to optimise workbook performance.
How to reduce dashboard load times.
How to use Tableau Prep.
How to automate data preparation.
How to integrate Python with Tableau.
How to integrate R with Tableau.
How to embed Tableau dashboards into websites.
How to implement row-level security.
How to build enterprise BI solutions.
How to tell compelling business stories with Tableau.
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.
How to install Qlik Sense Desktop.
How to create your first app.
How to connect to Excel.
How to connect to CSV files.
How to connect to SQL Server.
How to connect to Oracle databases.
How to connect to PostgreSQL.
How to connect to cloud databases.
How to navigate the Qlik Sense Hub.
How to publish an app.
How to use the Data Manager.
How to use the Data Load Editor.
How to load multiple files.
How to concatenate tables.
How to join tables.
How to keep tables separate.
How to rename fields.
How to change data types.
How to filter records during load.
How to reload data.
How to write a Qlik load script.
How to use Resident Load.
How to use Preceding Load.
How to create variables.
How to use LET and SET.
How to create calculated fields.
How to use IF statements.
How to use mapping tables.
How to use ApplyMap().
How to debug a load script.
How to build a star schema.
How to avoid synthetic keys.
How to remove circular references.
How to use link tables.
How to build calendar tables.
How to create master dimensions.
How to create master measures.
How to create master items.
How to optimise the data model.
How to troubleshoot associations.
How to write expressions.
How to use Sum().
How to use Avg().
How to use Count().
How to use Count Distinct().
How to use Aggr().
How to use Only().
How to use Above().
How to use Below().
How to create conditional expressions.
How to write Set Analysis expressions.
How to compare years.
How to calculate Year-to-Date values.
How to calculate Month-to-Date values.
How to calculate Quarter-to-Date values.
How to compare current vs previous year.
How to ignore selections.
How to create dynamic filters.
How to create rolling 12-month calculations.
How to optimise Set Analysis.
How to build a KPI object.
How to create bar charts.
How to create line charts.
How to create combo charts.
How to create pie charts.
How to create scatter plots.
How to create treemaps.
How to create pivot tables.
How to create maps.
How to create gauges.
How to create sheets.
How to build executive dashboards.
How to add filters.
How to create bookmarks.
How to use alternate states.
How to create drill-down groups.
How to add custom themes.
How to make dashboards responsive.
How to create storytelling presentations.
How to optimise dashboard performance.
How to publish apps to Qlik Cloud.
How to share dashboards securely.
How to schedule data reloads.
How to automate refreshes.
How to create spaces.
How to manage permissions.
How to use Qlik AutoML.
How to use Insight Advisor.
How to monitor app usage.
How to administer Qlik Enterprise.
How to optimise app performance.
How to reduce memory usage.
How to create reusable load scripts.
How to integrate REST APIs.
How to connect to web services.
How to implement row-level security.
How to use section access.
How to build enterprise BI solutions.
How to automate data pipelines.
How to tell compelling business stories with Qlik Sense.
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.
How to access Looker.
How to log into Looker via Google Cloud.
How to navigate the Looker interface.
How to explore existing dashboards.
How to view Looks (saved queries).
How to understand Explores.
How to switch between projects.
How to search dashboards.
How to set user preferences.
How to understand Looker roles and permissions.
How to use an Explore.
How to select fields in Explore.
How to apply filters in Explore.
How to group data by dimensions.
How to aggregate measures.
How to sort results.
How to limit result rows.
How to drill into data.
How to pivot data.
How to save an Explore as a Look.
How to create a Look.
How to edit a Look.
How to schedule a Look.
How to download Look results.
How to share a Look.
How to embed a Look.
How to duplicate a Look.
How to organize Looks into folders.
How to set Look permissions.
How to delete a Look.
How to create a dashboard.
How to add tiles to dashboards.
How to connect Explores to dashboards.
How to add filters to dashboards.
How to create dashboard links.
How to schedule dashboard delivery.
How to build executive dashboards.
How to customize dashboard layout.
How to embed dashboards.
How to share dashboards securely.
How to define a LookML project.
How to create a view file.
How to define a model file.
How to connect Looker to a database.
How to define dimensions.
How to define measures.
How to create derived tables.
How to use SQL in LookML.
How to validate LookML code.
How to deploy LookML changes.
How to create joins in LookML.
How to define relationships between views.
How to build persistent derived tables (PDTs).
How to optimize SQL queries.
How to create complex measures.
How to use templated filters.
How to use parameterized fields.
How to create conditional logic in LookML.
How to manage multiple environments.
How to version control LookML with Git.
How to design a semantic layer.
How to build a star schema in Looker.
How to optimize joins for performance.
How to avoid fan-out issues.
How to manage many-to-many relationships.
How to structure reusable views.
How to define aggregate awareness.
How to handle null values.
How to normalize data sources.
How to document data models.
How to build bar charts.
How to build line charts.
How to build scatter plots.
How to build pivot tables.
How to build heatmaps.
How to create KPI tiles.
How to create funnel charts.
How to use table calculations.
How to build cohort analysis.
How to create trend analysis dashboards.
How to set user roles.
How to configure permissions.
How to implement row-level security.
How to restrict data access by user.
How to audit user activity.
How to manage content folders.
How to enforce data governance policies.
How to certify data models.
How to manage data access layers.
How to secure embedded analytics.
How to connect Looker to BigQuery.
How to integrate Looker with APIs.
How to embed Looker in applications.
How to automate data refreshes.
How to schedule data deliveries.
How to integrate Looker with Slack.
How to export data to Google Sheets.
How to use Looker webhooks.
How to monitor query performance.
How to build scalable enterprise BI solutions.
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.
How to access Looker Studio.
How to create your first report.
How to connect Google Sheets.
How to connect Google Analytics.
How to connect BigQuery.
How to connect CSV files.
How to connect Google Ads.
How to navigate the report editor.
How to switch between edit and view mode.
How to share a report.
How to add a data source.
How to edit a data source.
How to blend multiple data sources.
How to refresh data connections.
How to replace a data source.
How to manage data credentials.
How to connect to SQL databases.
How to connect to third-party connectors.
How to use community connectors.
How to troubleshoot broken data sources.
How to rename fields.
How to change data types.
How to create calculated fields.
How to use CASE statements.
How to create custom metrics.
How to create date fields.
How to filter data at source level.
How to aggregate metrics.
How to handle null values.
How to create parameters.
How to add a chart.
How to add a table.
How to add scorecards.
How to add time series charts.
How to add pie charts.
How to add bar charts.
How to add geo maps.
How to add scatter plots.
How to add pivot tables.
How to add text boxes.
How to create a dashboard layout.
How to use theme settings.
How to format colors and fonts.
How to align components.
How to use grids and guides.
How to create multi-page reports.
How to design executive dashboards.
How to create mobile-friendly layouts.
How to use containers.
How to create visual hierarchy.
How to add date range filters.
How to add dropdown filters.
How to add search filters.
How to add slider controls.
How to apply filter controls globally.
How to create report-level filters.
How to create chart-level filters.
How to sync filters across pages.
How to reset filters.
How to use advanced filter logic.
How to write calculated fields.
How to calculate conversion rate.
How to calculate ROI.
How to calculate CTR.
How to calculate growth rate.
How to calculate year-over-year change.
How to create running totals.
How to calculate averages.
How to create conditional metrics.
How to use regex formulas.
How to create trend analysis charts.
How to build funnel visualizations.
How to create cohort charts.
How to build KPI dashboards.
How to visualize geographic data.
How to compare time periods.
How to show ranking charts.
How to build engagement dashboards.
How to highlight anomalies.
How to create storytelling dashboards.
How to share reports with users.
How to set viewer vs editor permissions.
How to publish reports.
How to embed reports in websites.
How to export reports as PDF.
How to schedule email delivery.
How to collaborate in real-time.
How to comment on reports.
How to manage access control.
How to duplicate reports safely.
How to use community visualizations.
How to use BigQuery SQL custom queries.
How to optimize report performance.
How to reduce data loading time.
How to handle large datasets.
How to use blended data performance tuning.
How to build enterprise dashboards.
How to integrate Google Sheets automation.
How to use API-driven reporting.
How to build automated business intelligence systems.
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.
How to access Amazon QuickSight.
How to sign up for QuickSight on AWS.
How to create your first dataset.
How to connect to AWS S3.
How to connect to Amazon RDS.
How to connect to Amazon Redshift.
How to connect to Athena.
How to upload a file dataset.
How to navigate the QuickSight console.
How to create your first analysis.
How to connect to SQL databases.
How to connect to cloud data warehouses.
How to import CSV files.
How to use SPICE in QuickSight.
How to manage SPICE capacity.
How to use direct query mode.
How to refresh datasets.
How to schedule data refreshes.
How to manage dataset permissions.
How to troubleshoot data connection issues.
How to clean data in QuickSight Prep.
How to rename fields.
How to change data types.
How to create calculated fields.
How to filter datasets.
How to join datasets.
How to append datasets.
How to aggregate data.
How to handle null values.
How to build curated datasets.
How to write calculated fields.
How to use ifelse() functions.
How to use sum() and avg().
How to calculate profit margins.
How to calculate growth rates.
How to calculate year-over-year change.
How to create running totals.
How to use level-aware calculations.
How to create conditional metrics.
How to create custom KPIs.
How to create bar charts.
How to create line charts.
How to create combo charts.
How to create pie charts.
How to create donut charts.
How to create scatter plots.
How to create heat maps.
How to create pivot tables.
How to create KPI visuals.
How to create funnel charts.
How to create an analysis.
How to build dashboards.
How to add multiple sheets.
How to link visuals.
How to create drill-downs.
How to create drill-through actions.
How to add filters.
How to sync filters.
How to use parameters.
How to design executive dashboards.
How to add filter controls.
How to add date range controls.
How to use dropdown filters.
How to create custom actions.
How to highlight data points.
How to enable cross-filtering.
How to create dynamic titles.
How to build responsive dashboards.
How to use toggle views.
How to add tooltips.
How to perform cohort analysis.
How to build sales performance dashboards.
How to perform trend analysis.
How to identify anomalies.
How to build forecasting visuals.
How to segment customers.
How to analyse churn.
How to calculate LTV (lifetime value).
How to perform funnel analysis.
How to build operational dashboards.
How to set up IAM roles.
How to manage QuickSight permissions.
How to implement row-level security.
How to create user groups.
How to share dashboards securely.
How to manage datasets access.
How to audit usage.
How to control SPICE access.
How to encrypt data sources.
How to comply with AWS security standards.
How to integrate with AWS Glue.
How to connect to AWS Lambda.
How to use Athena SQL queries.
How to connect to Redshift clusters.
How to embed QuickSight dashboards.
How to use APIs for automation.
How to schedule report delivery.
How to monitor performance.
How to scale QuickSight usage.
How to build enterprise BI solutions on AWS.
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.
Lloyds Banking Group
Barclays
HSBC
NatWest Group
Santander UK
Standard Chartered
Nationwide Building Society
Virgin Money
Metro Bank
Close Brothers
Aviva
AXA UK
Direct Line Group
Admiral Group
Legal & General
Zurich UK
Hiscox
RSA Insurance
Bupa Global
Markel UK
Tesco
Sainsbury’s
ASDA
Morrisons
Marks & Spencer
John Lewis Partnership
Ocado Group
Amazon UK
Argos (Sainsbury’s Group)
Next PLC
Rolls-Royce
BAE Systems
Jaguar Land Rover
Bentley Motors
Aston Martin
Siemens UK
GE Aerospace UK
British Steel
Schneider Electric UK
Caterpillar UK
NHS Digital
NHS England
AstraZeneca UK
GSK (GlaxoSmithKline)
Pfizer UK
Roche UK
Johnson & Johnson UK
Bayer UK
Boots UK
Bupa
Deloitte UK
PwC UK
EY UK
KPMG UK
Accenture UK
Capgemini
Cognizant UK
Infosys UK
Wipro UK
Tata Consultancy Services (TCS UK)
Google UK
Microsoft UK
Amazon Web Services UK
Meta UK
Salesforce UK
Oracle UK
Snowflake UK
Databricks UK
Adobe UK
IBM UK
Transport for London (TfL)
Network Rail
British Airways
EasyJet
Ryanair UK
Heathrow Airport
Gatwick Airport
DHL UK
Royal Mail
Uber UK
UK Home Office
HMRC
Ministry of Justice
Department for Work and Pensions (DWP)
UK Ministry of Defence
Office for National Statistics (ONS)
NHS Business Services Authority
UK Parliament Digital Service
Local Government Digital Services
Cabinet Office
BT Group
Vodafone UK
Sky (Comcast)
ITV
BBC
Channel 4
Centrica (British Gas)
National Grid
Scottish Power
SSE PLC
Across all 100 companies:
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)
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)