Accelerating Outcomes in Big Data, IIoT/IoT, and AI/MLTalking AI with Hashmap

July 2018

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We accelerate innovative business outcomes in BIG DATA, IIOT/IOT, and AI/ML

with a combination of PEOPLE, PROCESS, AND TECHNOLOGY

enabling END-TO-END SOLUTION DESIGN, DEVELOPMENT, & DEPLOYMENT

HASHMAP : WHAT WE DO

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Hashmap Corporate Snapshot

–Founded in 2012 to provide Big Data Consulting

–HQ in USA (Roswell, GA) with offices in Houston,

Canada, and India

–Sole focus has always been Big Data & IIoT/IoT

–Business model is 100% consulting services and

software engineering services (we do NOT resell

hardware, software, or subscriptions)

–Subcontract our services - you make $$$

HASHMAP : ABOUT US

HASHMAP QUICK STATS

ATLANTA

1000 Holcomb Woods Parkway

Building 100, Suite 118

Roswell, GA 30076

HOUSTON

24275 Katy Freeway

Suite 400

Katy, TX 77494

INDIA

Midas Tower, Plot # 44,

RGIP Phase 1,

Hinjewadi, Pune, Maharashtra, India

hashmapinc.com

Consulting Services

-Big Data, IIoT/IoT, AI/ML

-Domain Advisement,

Strategy, Architecture,

Data Engineering, Solution

Consulting, and

Application Development

OUR SERVICES FOCUS AREAS

Accelerator Services

-Ready-to-run, engineered,

template-based approach

-Tempus IIoT/IoT

- Cloud – Edge – ML

- Industrial, OPC, WITSML

Managed Services

- and “As a Service”

Models

-Architecture, Admin,

Optimization,

Automation,

Improvement

CANADA

4145 North Service Road

2nd floor

Burlington, Ontario L7L6A3

HASHMAP : ABOUT US 4

170

125

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CONSULTING PROJECTS

COMBINED CUSTOMERS

INDUSTRIESOil & Gas

Financial Services

Technology

Manufacturing

Insurance

Retail

Pharma

Healthcare

Communications

Power & Utilities

Digital Media

ROW

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PRESENTED BY DATABRICKS AT SPARK - AI SUMMIT 2018 5

Only a small % of enterprises are successful with AI & ML

PRESENTED BY DATABRICKS AT SPARK - AI SUMMIT 2018 6

Everyone Else Faces Major Challenges

That Slow Down AI/ML Projects

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DATA IS NOT READY FOR ANALYTICS

A ZOO OF AI/ML FRAMEWORKS

IT IS HARD TO PRODUCTIONIZE AI/ML

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IIoT/IoT and Streaming Analytics– Tempus IIoT/IoT

Framework– Industrial control

systems integration– Time Series Dataset

Optimization– Edge Intelligence and

Edge Computing– Deep expertise in Kafka

and Spark Streaming– Data flow and data

operations pipelines

HASHMAP : CONSULTING

NoSQL& SQL

– Evaluation, comparison, use case-based implementation

– Optimization, Tuning, Performance Testing, and Benchmarking

– Automated data ingestion into Big Data platforms for SQL datasets

– Low Latency Operational Data Stores

Cloud and Platform Services– Container Orchestration

and Management– DevOps– Cloud Enablement and

Simplified Deployment– Data Virtualization– Security– Governance– Operations– Performance

Data Science, Analytics, AI, & ML– Rapid Analytics

Application Creation– Self Service ML– In Memory Analytics Grid– Discovery & Exploration– Data insights– Data Preparation– Predictive Analytics

Data Engineering & Data Pipelines– Data Integration– Data Quality and

Curation– Spark Data Pipelines– Data Warehousing, EDW

Enablement, Lake Shore Marts

– Single View and Customer 360

– Offloads and Data Archiving

– Enterprise Application Environments

– Batch and Real Time Ingestion

8HASHMAP : PROJECTS

POC to determine marketing content effectiveness using Natural Language Processing ”NLP” in order to better focus ongoing marketing spend and budget

CHALLENGE

Automated social feed ad content for data acquisition, data cleansing and curation, natural language processing, visualization and data export to provide content analysis, engagement analysis, and spend analysis

APPROACH

Provided quick visibility into marketing content effectiveness through engagement prediction, post clustering, and key word identification associated with engagement success

OUTCOME

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Integration of on-premise, real time streaming data sources including an enterprise historian with dynamic, predictive ML models to provide insights to field operations

CHALLENGE

Integrated real time data collection and a high speed message broker with the on-premise data store providing a dynamic streaming solution for automated ML pipelines

APPROACH

A production ready, secure solution allowing the data science team to quickly operationalize and productionize their ML models within hours

OUTCOME

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HASHMAP : OUTCOME & USE CASE ENABLEMENT

HASHMAP OUTCOME & USE CASE ENABLEMENT WORKSHOP

Attendees

Program Key Stakeholders (Business and IT)

Duration

1-2 days onsite, 1-2 days offsite

Onsite Agenda

⏤ Business Context – Detailed use case review

and success criteria

⏤ Architecture Review

⏤ Data Center / Cloud Review

⏤ Ongoing Operations

⏤ Program/Project Time Horizons and Enabling

Roadmap

⏤ Confirmation / Final Risk Identification /

Deliverables Discussion / Wrap up

Deliverables

⏤ Business Value Matrix and Detail for

Specific Use Cases

⏤ Conceptual Architecture (Edge/Facility and

Data Center/Cloud) and program/project

horizon mapping

⏤ Recommendations and Go-Forward Plan

Key Dimensions Reviewed in the Business Context Segment

⏤ Organizational Effect

⏤ Business Impact

⏤ Priority and Urgency

⏤ Expected Time to Deliver

⏤ Risks

⏤ Innovation or Cost Savings Focus and

Impact

⏤ User Population and Consumption

Patterns

⏤ Capability Assessment and Review

⏤ Datasets

⏤ Other Dependencies

⏤ Technologies/Tools in use/planned/vision

⏤ ML/AI requirements

⏤ Analytics and visualization requirements

UNDERSTANDING – COLLABORATION - STRATEGY – ROADMAP - ARCHITECTURE

Objectives

DESIGN, REFINE, DEVELOP, DELIVER with an

outcome-based focus

Facilitate discussion and documentation of…

⏤ Business Value

⏤ Solution Architecture

⏤ Ongoing Operations

⏤ Timeline/Horizons

Provide deliverables that…

⏤ Demonstrate business alignment

⏤ Outline initiatives, priorities, and time horizons

⏤ Highlight expected value

HASHMAP : OUTCOME & USE CASE ENABLEMENT 11

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Review and Field Testing

HASHMAP : LABS

EdgeIntelligence

BlockchainEnablement

IndustrialDeep Learning

ComputerVision

ContainerOrchestration

Self ServiceML

13HASHMAP : LABS

In hazardous areas such as an Oilfield Drilling Rig, a Manufacturing Plant, or Heavy Equipment facility, it is important to understand the exposure of personnel to the riskiest areas. Gathering this data is crucial in understanding the exposure for improvements in operational processes and risk mitigation.

CHALLENGE

Using a convolutional neural network (image classification algorithm) applied to the whole image at a single point in time, several frames can be analyzed per second. By splitting a video image down into representative frames in real time at the edge, we are able to transmit only the events, rather than an entire image or video segment.

APPROACH

By applying real-time object detection, risk assessments and mitigation can be undertaken before the occurrence of a significant safety incident. By including safety related KPIs in a performance tracking program, organizations can have a holistic performance target in terms of both efficiency and safety.

OUTCOME

Utilizing a small edge device such as an Nvidia Jetson SoC (system on a chip) or a a ruggedized device, running a pre-trained object-detection algorithm allows the identification of objects of interest and the confidence of the identification. Based on a configurable threshold, events can be generated and transmitted over MQTT/CoAP or any appropriate IoT protocol.

SOLUTION

Next StepsContact Hashmap directly to discussopportunities to partner

Kelly KohlleffelVP Sales & Marketing(713) 628-6030kelly@hashmapinc.comlinkedin.com/in/kellykohlleffel

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