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Insights

Perspectives on data, analytics and the industries they change.

Articles from the IntelliCompute team — from cloud data warehousing and process intelligence to what analytics means for oil & gas, banking, retail and manufacturing.

AI PILOTS → THE P&L THE GAP IS THE OPERATING MODEL PILOTS THAT “WORK” HAND-CARRIED DATA · NO OWNER · NO CONTROLS Operating model FOUR GATES · BUILT ONCE, NOT PER PILOT Decision owner Governed data path Sequenced portfolio Assurance built in IN THE P&L Owned · governed · monitored THE SHORTEST CREDIBLE PATH RUNS THROUGH THE OPERATING MODEL, NOT ANOTHER PILOT

Featured · AI & Analytics

Why Most AI Pilots Never Reach the P&L

Boardroom ambition has outrun data maturity. The shortest credible path from pilot to production runs through the operating model: an owner, a governed data path, a sequenced portfolio, assurance.

Read article 3 min read
AI PILOTS → THE P&L THE GAP IS THE OPERATING MODEL PILOTS THAT “WORK” HAND-CARRIED DATA · NO OWNER · NO CONTROLS Operating model FOUR GATES · BUILT ONCE, NOT PER PILOT Decision owner Governed data path Sequenced portfolio Assurance built in IN THE P&L Owned · governed · monitored THE SHORTEST CREDIBLE PATH RUNS THROUGH THE OPERATING MODEL, NOT ANOTHER PILOT

AI & Analytics

Why Most AI Pilots Never Reach the P&L

Boardroom ambition has outrun data maturity. The shortest credible path from pilot to production runs through the operating model: an owner, a governed data path, a sequenced portfolio, assurance.

3 min read
DATA ENGINEERING vs DATA SCIENCE PLUMBERS + ARTISTS Data Engineering THE PLUMBERS · DESIGN THE DATA FLOW Pipelines & architectureC++ · Python · Scala · JavaAPIs · middlewareGovernance · quality checks Data Science THE ARTISTS · TELL THE DATA STORY Modelling & storytellingMaths · statistics · CSAI · machine learningBusiness insights ALLIANCE NOT "DO IT ALL" 85% OF BIG DATA PROJECTS FAIL (GARTNER 2017) · 70% OF DIGITAL TRANSFORMATIONS FAIL (McKINSEY) THE LINCHPIN: ENGINEERS + SCIENTISTS TOGETHER

Data Engineering & Cloud

Data Engineering vs Data Science: Which One Saves the Business?

The difference between data engineering and data science — definitions, focus areas, responsibilities — and why an alliance of engineers and scientists beats a do-it-all data scientist.

5 min read
MANUFACTURING · 7 OPERATIONS DATA ENGINEERING + DATA SCIENCE DATA WAREHOUSE · SENSORS 1 Predictive maintenance 2 Real-time monitoring 3 Demand & inventory 4 Price optimisation 5 Supply chain 6 Product development 7 Worker safety

Manufacturing & Supply Chain

7 Manufacturing Operations that Data Engineering & Data Science will Revamp

Seven manufacturing operations data engineering and data science will transform — maintenance, real-time monitoring, forecasting, pricing, supply chain, product development and safety.

6 min read
OIL & GAS · MARKET GROWTH +16.2% YOY REVENUE · FORBES 2019 GROWTH POWERED BY ADVANCED ANALYTICS Exploration & production ENERGY DEMAND +50% BY 2050 Changing regulations COMPLIANCE · CARBON FOOTPRINT Supply chain efficiency FIND GAPS · OPTIMISE Real-time operations INSTANT INSIGHT · LESS DOWNTIME HEADWINDS: PRICE SWINGS · FOSSIL-FUEL UNCERTAINTY · TRADE STRATEGY ON SHIFTING SANDS → BUILT ON DATA

Oil & Gas

Implementing Advanced Analytics for Oil & Gas Market Growth

How advanced analytics helps oil & gas companies bolster exploration and production, keep pace with changing regulations, connect the supply chain and track operations in real time.

5 min read
OIL & GAS · DATA WAREHOUSING ONE CONSISTENT SOURCE HETEROGENEOUS DATA Exploration Production Legacy systems Field sensors Finance 1980s → 1990s → TODAY Data Warehouse MULTIDIMENSIONAL · CONSOLIDATED · CONSISTENT EVERY BUSINESS UNIT Operations Compliance & reporting Planning Management ACCURATE · SHARED · REAL-TIME (NEXT) INTEGRATION + INFORMATION SHARING → BUSINESS PERFORMANCE

Oil & Gas

Advanced Analytics in Oil & Gas: Unlocking the Potential with Data Warehousing

Why data warehousing has become the backbone of advanced analytics in oil & gas — consolidating heterogeneous data, simplifying integration and enabling consistent sharing across business units.

4 min read
PREDICTIVE MAINTENANCE · OIL & GAS CATCH THE BREAKDOWN BEFORE IT HAPPENS SENSOR PARAMETERS Temperature Moisture Noise Vibration Electric current ASSET CONDITION · CONTINUOUS MONITORING PRE-DEFINED THRESHOLD SHUTDOWN (AVOIDED) Failure predicted · 9 days out ACTIONS Schedule maintenancePrioritise repairsAvoid shutdownPlan capex "DATA IS THE NEW OIL" · UPSTREAM · MIDSTREAM · DOWNSTREAM

Oil & Gas

Predictive Analytics in Oil & Gas Industry

Why data is becoming the oil industry's most valuable resource, and how predictive analytics and predictive maintenance catch breakdowns early, schedule repairs and guide capital decisions.

5 min read
OIL & GAS · ADVANCED ANALYTICS FOUR AREAS THAT PAY OFF SILOED · UNSTRUCTURED DATA INTEGRATION Reservoir management LET RESERVOIRS TALK 01 Hydrocarbon production ROBOTS · DRONES · ANALYTICS 02 Production optimisation AI + ML AMID PRICE SWINGS 03 ESP failure prediction MULTIVARIATE STATISTICS 04 VALUE · VOLUME · VERACITY · VELOCITY · VARIETY · COMPLEXITY

Oil & Gas

Oil & Gas Industry to Energise itself with Advanced Analytics-powered Growth

Data integration is the oil & gas industry's biggest hurdle. Four areas where advanced analytics pays off — reservoirs, hydrocarbon production, production optimisation and ESP failures.

5 min read
BANKING · PREDICTIVE → PRESCRIPTIVE 10 APPLICATIONS TRANSACTIONS CUSTOMERS · RISK PREDICTIVE What will happen? PRESCRIPTIVE What should we do? 01 Financial mgmt 02 Fraud prevention 03 Application screening 04 Liquidity planning 05 Acquisition & retention 06 Buying habits 07 Loan approval 08 Cross-selling 09 Lifetime value 10 CRM AI · MACHINE LEARNING · BIG DATA · DATA MINING

Banking & Finance

10 Ways the Future of Banking Is Predictive and Prescriptive

Ten applications of predictive and prescriptive analytics in banking — financial management, fraud prevention, screening, liquidity, acquisition, loans, cross-selling, lifetime value and CRM.

5 min read
DATA VISUALIZATION · RETAIL ONE PICTURE FOR EVERY TEAM BIG DATA + COMPANY DATA Sales by region Demographics Social media Store & stock VISUAL ANALYTICS DEMAND FORECAST RANGE ANALYSIS STORE CLUSTERS · SPACE PLANNING SHARED ACROSS TEAMS MerchandisingSupply chainMarketingITFinance PATTERNS · OUTLIERS · TRENDS → DATA-DRIVEN DECISIONS

Retail & Consumer

Top 5 Data Visualization Trends that Revitalize the Future of Retail

How data visualization and visual analytics are reshaping retail — forecasting demand shifts, uniting business and IT teams, blending big data with company data, and managing the retail flow.

5 min read
DATA QUALITY MANAGEMENT TOOLS · PROCESSES · PEOPLE RAW DATA INCOMPLETE · INACCURATE · UNRELIABLE DATA QUALITY GATE Solid data designRules & metricsData standardsMonitoringData architects PROACTIVE > REACTIVE HIGH-QUALITY DATA Less wasted resourcesHigher-quality leadsRaw → meaningful dataCompetitive edge 1% FLAWED DATA CAN SINK A CAMPAIGN COST OF MAINTAINING QUALITY < COST OF USING POOR-QUALITY DATA

Data Engineering & Cloud

Evolution of Data Quality Management and Business Intelligence

Why data quality management cannot be separated from analytics — four reasons it matters, and how to implement it with the right data design, architects, processes and people.

5 min read
FMCG · 2020 FROM PRODUCT TO CONSUMER DYNAMIC CONSUMER BEHAVIOUR EXPLORING · WAVERING LOYALTY CHANNEL TRENDS BIG DATA · ML · AI Personalisation Real-time behaviourPurchase habitsCustomer insights WINNING OPERATING MODEL Customised productsTHAT SELLSupply chainCONSUMER-LEDProduct managementINTELLIGENT INSIGHTSAgileREDUCED VULNERABILITY FOCUS: PRODUCT CONSUMER

Retail & Consumer

Why FMCG Is Moving Fast on Data Analytics

Consumer behaviour keeps shifting. How FMCG companies are adopting big data, machine learning and AI to personalise products, understand real-time habits and stay agile.

2 min read
MATERIAL HANDLING · MANUFACTURING VISIBILITY ACROSS THE VALUE CHAIN PLANT MATERIAL FLOW · EQUIPMENT BIG DATA · MACHINE LEARNING · AI DATA VIRTUALIZATION · VISUAL PATTERN RECOGNITION Operations decisions MIN COST · MAX THROUGHPUT COMPLEX TRADE-OFFS Material performance INSPECTION · MAINTENANCE · TESTING DATA-DRIVEN SUPPLY CHAIN · PRODUCTIVITY · PROFITABILITY

Manufacturing & Supply Chain

Data Analytics is Revolutionizing Material Handling and Management Operations

How manufacturers apply data analytics, machine learning and big data to material handling — better operations decisions and monitored material and equipment performance.

2 min read
DATA SCIENCE IN BFSI DATA AS FUEL EVERY OPERATION GENERATES DATA DATA SCIENCE · ANALYTICS · BUSINESS INTELLIGENCE Risk Management PREDICT LOSS FREQUENCY · GAUGE SEVERITY FRAUD DETECTION · TRUST Predictive Analytics CUSTOMER TRENDS · SOCIAL + OTHER DATA CUSTOMER ANALYTICS Personalised Marketing SPEECH · ML · NLP · CAMPAIGNS CUSTOMISED SERVICES BFSI · PRIME END USER OF ADVANCED ANALYTICS

Banking & Finance

Why the Financial Sector is Banking on Advancements in Data Science

Data has always been the financial sector's fuel. How BFSI is applying data science to risk management, predictive analytics and personalised marketing.

3 min read
DATA ENGINEERING & DATA SCIENCE FIVE TRENDS · ADOPTION ↑ 01 NLP + data science VOICE · TEXT · MARKET INTEL 02 AI-powered IoT PREDICT FAILURES · UPTIME 03 ML automation CLEANING · PREDICTIVE ANALYTICS 04 Privacy & security ANOMALY DETECTION 05 Cloud data warehouses FLEXIBLE · CONNECTED · CHEAPER ADOPTION 2016 → 2020 → CLOUD-ERA DATA ENGINEERING ON-PREMISES WAREHOUSES CLOUD DW

Data Engineering & Cloud

Five Hottest Trends that are Reshaping Data Engineering & Data Science

NLP integration, AI-powered IoT, machine-learning automation, data privacy and security tooling, and cloud data warehouses — the five trends reshaping data engineering and data science.

5 min read
HR ANALYTICS START AT THE BOTTOM OF THE PYRAMID CREATIVE DATA SOURCES HR systemsBiometricsIntranet logsSmart-office sensorsExternal data DESCRIPTIVE what happened DIAGNOSTIC why it happened PREDICTIVE what will happen PRESCRIPTIVE how to influence it BOTTOM-UP OUTCOMES Reduce hiring biasFind performance driversImprove relationshipsPredict attrition EXPLAINABLE RESULTS · INTERPRETABLE MODELS APPROACH > TOOLS

AI & Analytics

Here's how the HR function can be transformed with Data Analytics

Three suggestions for a smarter, data-driven HR function — get creative with data sources, use the full analytics toolbox bottom-up, and put approach before tools.

3 min read
DATA GOVERNANCE FOR ML OPENING THE BLACK BOX DISPARATE SOURCES Structured Unstructured Huge volumes Multiple systems DATA GOVERNANCE AvailabilityUsabilityIntegritySecurityEffectiveness ML MODEL TRANSPARENT · TRUSTED Decision RELIABLE · EXPLAINABLE GDPR-COMPLIANT WITHOUT GOVERNANCE→ misleading information · unforeseen overheads · irrevocable consequences WITH GOVERNANCE→ security · safety · full potential of ML

Data Engineering & Cloud

AI & ML thrive on data, but without Data Governance, they can't go far

Machine learning is only as trustworthy as the data behind it. Why a robust data governance framework — availability, usability, integrity, security — is the foundation for AI and ML success.

2 min read
PROCUREMENT ANALYTICS FIVE WAYS TO BUY BETTER INPUTS Supplier performance Market pricing & risk Shipping & carrier data Social / text (unstructured) SPEND ANALYTICS PREDICTIVE MODEL · BENCHMARKS SUPPLIER SCORECARD Supplier ASupplier BSupplier C SPEND vs PEER GROUP · REAL TIME 01Sourcing value02Evolving demand03Best price & quality04Internal + external spend05Unstructured data

Manufacturing & Supply Chain

5 ways Data Analytics can transform the Procurement Process

Five ways procurement teams use data analytics to buy better — smarter sourcing, evolving demand, best price and quality, internal and external spend views, and unstructured data.

3 min read
DATA-CENTRIC SALES OPERATIONS UNDERSTAND EACH CUSTOMER INDIVIDUALLY VALUE ENGAGEMENT → MOST PROFITABLE AT RISK 01 Segmentation AGE · GEOGRAPHY · HABITS 02 Product development SURVEYS · FEEDBACK · TESTING 03 Agility RETAIN · PREDICT · ADAPT 04 Disruption DATA AT THE CORE DRIVE MORE SALES RETENTION · LOYALTY · INNOVATION

AI & Analytics

Strategizing Sales Operations with Data Analytics

Why data-centric companies win: how data analytics transforms sales strategy through segmentation, product development, agility and disruption — and puts customers first.

4 min read
AI IN DISTRIBUTION THE SYSTEM GROWS SMARTER OVER TIME ANALYSE APPLY ASSESS ACQUIRE AI + ML SIGNALS Purchasing patterns Newsletter downloads Website re-orders Order history OUTCOMES Prioritised prospects WHO TO SPEND TIME ON Product suggestions SIMILAR & RELATED Fewer errors SEAMLESS EXPERIENCE Order size ↑ · Margin ↑ BETTER RELATIONSHIPS SMARTER OVER TIME →

Retail & Consumer

Leveraging the potential of AI in the Distribution Industry

AI is no longer reserved for the biggest companies. How distributors and wholesalers use AI and machine learning to prioritise customers, recommend products, cut errors and grow order size.

2 min read
AI IN LOGISTICS & SUPPLY CHAIN PRODUCTION → DELIVERY AI ML · DL Predictive CAPABILITIES Robotics WAREHOUSE Big data ROUTE OPTIMISATION Computer VISION Autonomous VEHICLES Demand FORECASTING PLATOONING · AUTOPILOT SUPPLIER INSIGHTSAUDITS · DELIVERY · CREDIT CUSTOMER EXPERIENCEVOICE TRACKING

Manufacturing & Supply Chain

Revolutionizing Global Logistics and Supply Chain Management with the power of AI

How AI is transforming logistics and supply chain — predictive capabilities, robotics, big data, computer vision, autonomous vehicles, demand forecasting, supplier insights and transportation.

4 min read
S3 → ATHENA → QUICKSIGHT SERVERLESS SQL ON ARCHIVED DATA Amazon S3 BUCKET · FOLDER STRUCTURED + UNSTRUCTURED METADATA Athena SCHEMA · AD-HOC SQL CREATE TABLE … FROM S3 BUCKET DATA SELECT * FROM archive; PERMISSIONS QUICKSIGHT · SPICE ATHENA FORMATS CSVTSVJSONPARQUETORC

Data Engineering & Cloud

Connecting Amazon QuickSight to Amazon S3 with Athena

How data archived in Amazon S3 is queried with Athena and visualised in QuickSight — creating buckets, defining schemas, setting permissions and building dashboards.

6 min read
AI ⊃ ML ⊃ DL INTERRELATED, YET DIFFERENT ARTIFICIAL INTELLIGENCE MACHINE LEARNING DEEP LEARNING Artificial Intelligence Human intelligence displayed by machines McCARTHY · 1955 Machine Learning An approach to achieve AI — learns from data SAMUEL · 1959 Deep Learning A technique for implementing ML — finds features itself BRAIN-INSPIRED ML · FEATURES SPECIFIED MANUALLY DL · FEATURES DISCOVERED AUTOMATICALLY

AI & Analytics

How are AI, ML & Deep Learning interrelated, yet different?

Artificial Intelligence, Machine Learning and Deep Learning are often used interchangeably. Here is how they nest inside one another — and what actually sets them apart.

2 min read
RETAIL INTELLIGENCE CUSTOMER IS KING SHELF · PLACEMENT CLICKS · CART · BUY SENSORS · VISION BUSINESS INTELLIGENCE DEMANDFORECAST → Consumer behaviourTrend analysisTracking movesNon-performing SKUsProduct placement

Retail & Consumer

Implementing Data Intelligence in Retail. Is it worth it?

Why business intelligence matters in retail — understanding consumer behaviour, trend analysis, tracking customer moves, handling non-performing products and strategic product placement.

3 min read
SNOWFLAKE → QUICKSIGHT SPICE IN-MEMORY ENGINE Snowflake WAREHOUSE · MPP VALIDATECONNECTION Data set CUSTOM SQL · TABLE JOINS · CALC FIELDS SPICE DASHBOARD VISUALS · FILTERS · STORY A · CONSOLED · DATA SOURCEG · SPICEK · PUBLISH

Data Engineering & Cloud

Connecting Amazon QuickSight to a Snowflake Warehouse

Step-by-step: connecting Amazon QuickSight to a Snowflake data warehouse — data sources, custom SQL, SPICE, calculated fields, joins, visuals and publishing a dashboard.

3 min read
UPSTREAM Exploration · Production MIDSTREAM Processing · Storage · Transport DOWNSTREAM Refining · Distribution · Retail ADVANCED & OPERATIONAL DATA ANALYTICS Exploration accuracy Better decisions Machinery utilisation Supply & demand forecasting DATA VOLUME ↑ OIL & GAS VALUE CHAIN

Oil & Gas

How Advanced Data Analytics is helping out the Oil & Gas Industry

How advanced data analytics cuts cost and risk across upstream, midstream and downstream oil & gas — from exploration accuracy to supply and demand forecasting.

4 min read