Menu

Use-Cases & Analytics to drive BigData ROI

Resources with Skills & Experience

Roadmaps, PoCs & Deployments

BigData Tools Blueprints
 

Our solutions help customers align near, mid and long term selection of use-cases:

  • Identify use-cases and select appropriate datasets
  • Develop fixed scope Proof-of-Concepts
  • Ensure data quality to earn end-user trust
  • Develop analytics and deliver business value
  • Prove ROI and business value
  Library of Use-Cases:
arrowshape8 Business Functions
arrowshape8 Analytics & Insights
arrowshape8 Revenues & Costs Metrics
   
Choose a Use Case  
Customer 360 Marketing A / B Sales Lead Generation Product & Services Lifecycle Management
More   
Customer 360 program delivers a unified, consistent, continuous view of Customer aggregated from multiple touch points. Examples:

Customer
360 = C360

Customer Platforms:
  • Digital Store Fronts
  • Social Media Sites
  • Call Center
  • In-Person store visits
  • Mail Order
Operational Datasets:
  • Social Media
  • Product & Pricing
  • Demographics
  • CRM
  • Credit & Payments
Foundation: Big Data Platform & Key Functions
hortonworks   

Marketing A / B

Sales Lead Generation

Product & Services Lifecycle Management

Driving Market Share Expansion, Customer Retention, Repeat Purchase Cultivation, Competitors Marketing … all are objectives enhanced by fact-driven metrics obtained from Analytics & Insights.

Marketing A / B

A / B Testing + Analytics + Insights:
  • Hypothesis Testing
  • Single Variable Analysis
  • Success Metric Definition & Alignment
  • Volume & Statistical Significance Metrics
  • Test Group and Splits (Absolute Values & Ranges)
  • Randomization Levels
  • Documentation

Customer 360

Sales Lead Generation

Product & Services Lifecycle Management

How do you identify, measure and react to buying intent across a multi-touch Sales Process?

Gen-1 'lead generation' via metrics from online portals, email & inbound / outbound calling campaigns is the norm.

Sales Lead
Generation

'Gen-2' is all about 'Closed Loop' Analytics &Insights from Marketing to Lead Generation to Sale Closure.

Evolving from Gen-1 to Gen-2 features:
  • Attribution Analytics
  • Personalization & Engagement Scoring
  • Competitive Pricing Scoring
  • Sales Efficiency & Effectiveness Scoring
  • Traffic Increase Scoring
  • Lead Conversions
  • Deferrals & Rejection ‘Cause’ Scoring

Customer 360

Marketing A / B

Product & Services Lifecycle Management

IoT: Internet of Things Successful IoT requires very lean, efficient, high-velocity and LOW cost processing systems

IoT solutions are being developed in our BigData Lab. sample functions & features:

Products Engineering & Services

  • Data Capture with reliability & speed
  • Ingestion Management via multiple formats & into multiple components: Spark, Storm, HBase etc.
  • Polyglot Persistence Models to create Insights
  • Feedback to Operational Systems, Service Delivery & Field Dispatches

Customer 360

Marketing A / B

Sales Lead Generation

We put together trained and experienced teams for BigData projects

On-Premise BigData Lab enables testing of designs, solution blue prints and integrated workflows by our Engineers

Right Skills
+
Proven Experiences
=
Successful Delivery Build a great team  


Technical Delivery Managers Solution Architects      Data Engineering DevOps & Hadoop Cluster Operations    

 

 

Technical Project Managers perform Gap Analysis and develop the Work Breakdown Structure (WBS) for key deliverables
Tech. Delivery
Managers
Methodology:
  • WBS by Function + Tasks : Time + Resource : Time
  • Solution Sets – readymade & pre-tested blueprints
  • Set 1: Data Lakes: Extraction from Sources & HDFS Ingestion
  • Set 2: Lakes Governance: Lifecycle, Access & Capacity Mgmt.
  • Set 3: Analytics & Insights: Exploration, Modeling & Integration
  • Set 4: Analytics & Insights integration with existing BI tools

Solution Architects

Data Engineering

DevOps & Hadoop Cluster Operations

Our Solution Architects specialize in major functional areas and utilize Best Practices & Gap Analysis to fulfill customer’s needs
Solution Architects
Methodology:
  • Templates: Scope / Requirements / Design(s)
  • Pre-Tested Configurations: Mix of tools & workflows
  • Set 1:   Data Lakes: Extraction from Sources & HDFS Ingestion
  • Set 2:   Lakes Governance: Lifecycle, Access & Capacity Mgmt.
  • Set 3:   Data Analytics:
    • Data Wrangling (Pig / Latin)
    • Pre-Computed Datasets
    • Spark, Storm, NoSQL data flows
    • HBase Key/Value Truth Sets
  • Set 4:   Data Engineering:
    • Data Security, Audit Trails
    • Operational Job queues
    • Data Archival & Lifecycle Mgmt.
edsworklogo1

Technical Delivery Managers

Data Engineering

DevOps & Hadoop Cluster Operations

Operationalization & Optimization role is required for BigData Platform: to ensure effective, balanced, secure and auditable use of Tools & Workflows
Data
Engineering
Methodology:
  • Templates: Operational Configurations by function
  • Monitoring: Multiple Job Execution Pipelines
  • Set 1:   Cluster / YARN Optimizations
    • YARN - Applications deployments
    • Performance &Throughput Mgmt.
  • Set 2:   Data Engineering:
    • Data Security, Audit Trails
    • Operational Job queues
    • Data Archival & Lifecycle Mgmt.
  • Set 3:   Data Lake Governance
    • Data Quality, Metadata, Lineage
    • Data Domain Specific Taxonomies
    • End-User Search via SOLR Indexing
    • Data Lifecycle Management

Technical Delivery Managers

Solution Architects

DevOps & Hadoop Cluster Operations

Our customers, often ask, us to manage their BigData Platforms (post build & deploy) on either Cloud or On-Premise … as internal resources & competencies are established
DevOps & Hadoop
Cluster Operations
Methodology:
Cluster Operations:
  • Knowledge Base of Trouble Shooting solutions
  • Best Practices based Solution Blueprints
  • Set 1:  Data Lake Operations  
    • Break / Fix “Level 1” Operational Support Services
    • SLA Management to Analytical Applications
    • Hadoop Cluster Resources Capacity ‘Q’ Mgmt.
    • User Access and Data Security
    • Data Archival and Purge Mgmt.

Technical Delivery Managers

Solution Architects

Data Engineering

In our BigData Lab, we develop, test, deliver solution sets: each set is a fully working component of the BigData Platform

orange_tab
Evaluate our solutions   

“ELT” or “ETL” for Data Lakes Hadoop Data & Applications Management Analytics & Insights Business Intelligence Integration

 

 

Technical Project Managers perform Gap Analysis and develop the Work Breakdown Structure (WBS) for key deliverables
 
E.L.T into
Data Lakes
Our Methodology:
  • Solution sets
  • Seminars & Knowledge Transfer Workshops
  • Solution Set 1: Fully featured Data Lake that is pre-assembled, pre-configured, pre-tested and scaled at deployment for ingest workloads:
  • Phase 1: Deliver robust E.L.T and data ingest
  • Phase 2: Add search or retrieval of datasets
  • Phase 3: Add Access & Data security

Phase 1

Phase 2

Phase 3

Hadoop Data & Applications Management

Analytics & Insights

Business Intelligence Integration

Up to 78% efficiencies with optimizations
  • Storage format: RC, Parquet, ORC, Text
  • Runtime values: YARN, TEZ, Slider
  • Compute: Spark, Storm, Cassandra, HBase
Hadoop Data & Application
Mgmt. Best Practices
Best Practices for Data & App. Mgmt.
orange_chart
bigdatatools3

"ELT" or "ETL" for Data Lakes

Analytics & Insights

Business Intelligence Integration

Our focus is Analytics for non-technical users
  • By Unifying: model design, scoring & running
  • By Scaling: using Spark on YARN/TEZ
  • By Common Patterns: pre-computed datasets
Data Analytics &
Business Insights
Five high-value analytics domains:
  • Predictive: negative or positive event occurrence
  • Prescriptive: prevent or facilitate desired outcome
  • Geospatial: mix time-series, locations & events
  • Textual: insights from unstructured text datasets
  • Operational: querying of near real-time data
bigdatatools3

"ELT" or "ETL" for Data Lakes

Hadoop Data & Applications Management

Business Intelligence Integration

We deliver a mix of NoSQL + Hive + HBase as a ‘serving’ layer to your existing front-end Business Intelligence capabilities

Customers existing decision systems based on ‘traditional’ Business Intelligence tools need to include BigData insights from Hadoop

Integration with
Business Intelligence
Our solution set 4 connects Hadoop & BI
  • HiveQL: Fetches data from Hive Tables
  • HBase: Fetches data from VERY LARGE datasets
  • Cassandra: Very fast Query service to BI tools
bigdatatools4

"ELT" or "ETL" for Data Lakes

Hadoop Data & Applications Management

Analytics & Insights

 

We help customers develop BigData capabilities, mitigate risks and initiate best practices

 

 

  BigData Platform:
Data Capture & Ingestion
Datalake Management
Analytics and Insights
BI integrations
Feedback to Applications
Self-Assess your Readiness   
Proof of Concepts of Fixed Scope & Time Data Lake Management Analytics & Digital Insights Gap Analysis & Roadmaps

 

 

 

 

Gap Analysis lays the foundation for creating near and long term ROI Fixed Scope PoC is often the most rewarding path to BigData value
 

Proof of Concepts of
Fixed Scope & Time

Our Methodology:

Quickstart PoC with prefabricated blueprints for deployment either on-premise or in Cloud

  • Hadoop Data Lakes
  • Batch and Streaming Data Ingestion
  • Ready-to-Use HiveQL, Pig / Latin ETL
  • Basic Analytics and Insights
  • Ready-to-Use Reporting (NoSQL)
  • Integration of NoSQL & RDBMS-SQL
  • Hadoop Platform operational Best Practices
  • Knowledge Transfer & Training for internal staff

Data Lake Management

Analytics & Digital Insights

Gap Analysis & Roadmaps

3 Critical functions are required in any BigData Processing Platform:
 

Data Lake
Management

Our Methodology:

Governance: Five Processes

  • Auditing – for access, by resource etc.
  • Lineage – dataset traceability origin to usage
  • Metadata – discover, search relevant data
  • Data Lifecycle – ingest, process, retire & purge
  • Stewardship & Curation – owner & cataloging

Data Management: Three Processes

  • Ingestion & Transmission (import / export)
  • Replication (across DCs, Hot / Warm / Cold)
  • Aggregation & Retention of datasets

Process Management: Three Processes

  • Cluster, Feed, Process specifications
  • Late Data Handling (back off, final)
  • Scheduling & Dependency Management

Proof of Concepts of Fixed Scope & Time

Analytics & Digital Insights

Gap Analysis & Roadmaps

Analytics & Insights from BigData platform requires specific capabilities:
 

Analytics &
Digital Insights

Our Methodology:

Identify Key Capabilities needed to support Business Value propositions:

  • Capability 1: High Quality (Clean) datasets
  • Capability 2: Metadata for datasets
  • Capability 3: Decision speed of organizations
  • Insights 1: Business User or Operations ?
  • Insights 2: New Services or Existing Services ?
  • Insights 3: Type: exploratory or hypothesis ?
  • Identify End-User Type: Casual, Primary, and Power Users and the top 3 or 4 queries
  • Knowledge Transfer & Training for internal staff

Proof of Concepts of Fixed Scope & Time

Data Lake Management

Gap Analysis & Roadmaps

21 Key functions – based on our best practices based BigData Maturity Curve help Customers assess their own readiness to achieve positive ROI
 

Gap Analysis
& Roadmaps

21 Key Functions: (a sample)

Data Lakes:

  • Data Capture from heterogeneous sources
  • Data Ingestion into multiple Hadoop tools
  • Data Management (Lifecycle, Security etc.)
  • Audit Trail, Security,
  • Data Quality, Metadata, Lineage etc.
  • Data Snapshots, Feeds, and Streaming

Analytics:

  • Transformations & Pre-Computed data
  • Modeling, Truth-Sets & Analytics
  • Digital Insights

Visualizations:

  • Spatial, Temporal, Longitudinal etc.
  • Analytic Dashboards & Feedback Loops

Proof of Concepts of Fixed Scope & Time

Data Lake Management

Analytics & Digital Insights

Copyright © 2017 Evaya Data Systems. All rights reserved.