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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&LTHE GAP IS THE OPERATING MODELPILOTS THAT “WORK”HAND-CARRIED DATA · NO OWNER · NO CONTROLSOperating modelFOUR GATES · BUILT ONCE, NOT PER PILOTDecision ownerGoverned data pathSequenced portfolioAssurance built inIN THE P&LOwned · governed · monitoredTHE 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&LTHE GAP IS THE OPERATING MODELPILOTS THAT “WORK”HAND-CARRIED DATA · NO OWNER · NO CONTROLSOperating modelFOUR GATES · BUILT ONCE, NOT PER PILOTDecision ownerGoverned data pathSequenced portfolioAssurance built inIN THE P&LOwned · governed · monitoredTHE 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 SCIENCEPLUMBERS + ARTISTSData EngineeringTHE PLUMBERS · DESIGN THE DATA FLOWPipelines & architectureC++ · Python · Scala · JavaAPIs · middlewareGovernance · quality checksData ScienceTHE ARTISTS · TELL THE DATA STORYModelling & storytellingMaths · statistics · CSAI · machine learningBusiness insightsALLIANCENOT "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 OPERATIONSDATA ENGINEERING + DATA SCIENCEDATA WAREHOUSE · SENSORS1Predictive maintenance2Real-time monitoring3Demand & inventory4Price optimisation5Supply chain6Product development7Worker 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 2019GROWTHPOWERED BY ADVANCED ANALYTICSExploration & productionENERGY DEMAND +50% BY 2050Changing regulationsCOMPLIANCE · CARBON FOOTPRINTSupply chain efficiencyFIND GAPS · OPTIMISEReal-time operationsINSTANT INSIGHT · LESS DOWNTIMEHEADWINDS: PRICE SWINGS · FOSSIL-FUEL UNCERTAINTY · TRADESTRATEGY 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 WAREHOUSINGONE CONSISTENT SOURCEHETEROGENEOUS DATAExplorationProductionLegacy systemsField sensorsFinance1980s → 1990s → TODAYData WarehouseMULTIDIMENSIONAL · CONSOLIDATED · CONSISTENTEVERY BUSINESS UNITOperationsCompliance & reportingPlanningManagementACCURATE · 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 & GASCATCH THE BREAKDOWN BEFORE IT HAPPENSSENSOR PARAMETERSTemperatureMoistureNoiseVibrationElectric currentASSET CONDITION · CONTINUOUS MONITORINGPRE-DEFINED THRESHOLDSHUTDOWN (AVOIDED)Failure predicted · 9 days outACTIONSSchedule 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 ANALYTICSFOUR AREAS THAT PAY OFFSILOED · UNSTRUCTUREDDATAINTEGRATIONReservoir managementLET RESERVOIRS TALK01Hydrocarbon productionROBOTS · DRONES · ANALYTICS02Production optimisationAI + ML AMID PRICE SWINGS03ESP failure predictionMULTIVARIATE STATISTICS04VALUE · 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 → PRESCRIPTIVE10 APPLICATIONSTRANSACTIONSCUSTOMERS · RISKPREDICTIVEWhat will happen?PRESCRIPTIVEWhat should we do?01Financial mgmt02Fraud prevention03Application screening04Liquidity planning05Acquisition & retention06Buying habits07Loan approval08Cross-selling09Lifetime value10CRMAI · 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 · RETAILONE PICTURE FOR EVERY TEAMBIG DATA + COMPANY DATASales by regionDemographicsSocial mediaStore & stockVISUAL ANALYTICSDEMAND FORECASTRANGE ANALYSISSTORE CLUSTERS · SPACE PLANNINGSHARED ACROSS TEAMSMerchandisingSupply chainMarketingITFinancePATTERNS · 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 MANAGEMENTTOOLS · PROCESSES · PEOPLERAW DATAINCOMPLETE · INACCURATE · UNRELIABLEDATA QUALITY GATESolid data designRules & metricsData standardsMonitoringData architectsPROACTIVE > REACTIVEHIGH-QUALITY DATALess wasted resourcesHigher-quality leadsRaw → meaningful dataCompetitive edge1% FLAWED DATA CAN SINK A CAMPAIGNCOST 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 · 2020FROM PRODUCT TO CONSUMERDYNAMIC CONSUMER BEHAVIOUREXPLORING · WAVERING LOYALTYCHANNEL TRENDSBIG DATA · ML · AIPersonalisationReal-time behaviourPurchase habitsCustomer insightsWINNING OPERATING MODELCustomised productsTHAT SELLSupply chainCONSUMER-LEDProduct managementINTELLIGENT INSIGHTSAgileREDUCED VULNERABILITYFOCUS:PRODUCTCONSUMER

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 · MANUFACTURINGVISIBILITY ACROSS THE VALUE CHAINPLANTMATERIAL FLOW · EQUIPMENTBIG DATA · MACHINE LEARNING · AIDATA VIRTUALIZATION · VISUAL PATTERN RECOGNITIONOperations decisionsMIN COST · MAX THROUGHPUTCOMPLEX TRADE-OFFSMaterial performanceINSPECTION · MAINTENANCE · TESTINGDATA-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 BFSIDATA AS FUELEVERY OPERATION GENERATES DATADATA SCIENCE · ANALYTICS · BUSINESS INTELLIGENCERisk ManagementPREDICT LOSS FREQUENCY · GAUGE SEVERITYFRAUD DETECTION · TRUSTPredictive AnalyticsCUSTOMER TRENDS · SOCIAL + OTHER DATACUSTOMER ANALYTICSPersonalised MarketingSPEECH · ML · NLP · CAMPAIGNSCUSTOMISED SERVICESBFSI · 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 SCIENCEFIVE TRENDS · ADOPTION ↑01NLP + data scienceVOICE · TEXT · MARKET INTEL02AI-powered IoTPREDICT FAILURES · UPTIME03ML automationCLEANING · PREDICTIVE ANALYTICS04Privacy & securityANOMALY DETECTION05Cloud data warehousesFLEXIBLE · CONNECTED · CHEAPERADOPTION2016 → 2020 →CLOUD-ERA DATA ENGINEERINGON-PREMISES WAREHOUSESCLOUD 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 ANALYTICSSTART AT THE BOTTOM OF THE PYRAMIDCREATIVE DATA SOURCESHR systemsBiometricsIntranet logsSmart-office sensorsExternal dataDESCRIPTIVEwhat happenedDIAGNOSTICwhy it happenedPREDICTIVEwhat will happenPRESCRIPTIVEhow to influence itBOTTOM-UPOUTCOMESReduce hiring biasFind performance driversImprove relationshipsPredict attritionEXPLAINABLE RESULTS · INTERPRETABLE MODELSAPPROACH > 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 MLOPENING THE BLACK BOXDISPARATE SOURCESStructuredUnstructuredHuge volumesMultiple systemsDATA GOVERNANCEAvailabilityUsabilityIntegritySecurityEffectivenessML MODELTRANSPARENT · TRUSTEDDecisionRELIABLE · EXPLAINABLEGDPR-COMPLIANTWITHOUT GOVERNANCE→ misleading information · unforeseen overheads · irrevocable consequencesWITH 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 ANALYTICSFIVE WAYS TO BUY BETTERINPUTSSupplier performanceMarket pricing & riskShipping & carrier dataSocial / text (unstructured)SPEND ANALYTICSPREDICTIVE MODEL · BENCHMARKSSUPPLIER SCORECARDSupplier ASupplier BSupplier CSPEND vs PEER GROUP · REAL TIME01Sourcing 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 OPERATIONSUNDERSTAND EACH CUSTOMER INDIVIDUALLYVALUEENGAGEMENT →MOST PROFITABLEAT RISK01SegmentationAGE · GEOGRAPHY · HABITS02Product developmentSURVEYS · FEEDBACK · TESTING03AgilityRETAIN · PREDICT · ADAPT04DisruptionDATA AT THE COREDRIVE MORE SALESRETENTION · 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 DISTRIBUTIONTHE SYSTEM GROWS SMARTER OVER TIMEANALYSEAPPLYASSESSACQUIREAI+ MLSIGNALSPurchasing patternsNewsletter downloadsWebsite re-ordersOrder historyOUTCOMESPrioritised prospectsWHO TO SPEND TIME ONProduct suggestionsSIMILAR & RELATEDFewer errorsSEAMLESS EXPERIENCEOrder size ↑ · Margin ↑BETTER RELATIONSHIPSSMARTER 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 CHAINPRODUCTION → DELIVERYAIML · DLPredictiveCAPABILITIESRoboticsWAREHOUSEBig dataROUTE OPTIMISATIONComputerVISIONAutonomousVEHICLESDemandFORECASTINGPLATOONING · AUTOPILOTSUPPLIER INSIGHTSAUDITS · DELIVERY · CREDITCUSTOMER 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 → QUICKSIGHTSERVERLESS SQL ON ARCHIVED DATAAmazon S3BUCKET · FOLDERSTRUCTURED + UNSTRUCTUREDMETADATAAthenaSCHEMA · AD-HOC SQLCREATE TABLE …FROM S3 BUCKET DATASELECT * FROM archive;PERMISSIONSQUICKSIGHT · SPICEATHENA FORMATSCSVTSVJSONPARQUETORC

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 ⊃ DLINTERRELATED, YET DIFFERENTARTIFICIAL INTELLIGENCEMACHINE LEARNINGDEEPLEARNINGArtificial IntelligenceHuman intelligence displayed by machinesMcCARTHY · 1955Machine LearningAn approach to achieve AI — learns from dataSAMUEL · 1959Deep LearningA technique for implementing ML — finds features itselfBRAIN-INSPIREDML · FEATURES SPECIFIED MANUALLYDL · 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 INTELLIGENCECUSTOMER IS KINGSHELF · PLACEMENTCLICKS · CART · BUYSENSORS · VISIONBUSINESS INTELLIGENCEDEMANDFORECAST →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 → QUICKSIGHTSPICE IN-MEMORY ENGINESnowflakeWAREHOUSE · MPPVALIDATECONNECTIONData setCUSTOM SQL · TABLEJOINS · CALC FIELDSSPICEDASHBOARDVISUALS · FILTERS · STORYA · 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

UPSTREAMExploration · ProductionMIDSTREAMProcessing · Storage · TransportDOWNSTREAMRefining · Distribution · RetailADVANCED & OPERATIONAL DATA ANALYTICSExploration accuracyBetter decisionsMachinery utilisationSupply & demand forecastingDATA 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