Nov 14, 2019

Data Managementin FlightSumeet Agrawal

Senior Director, Product Management

Sumeet AgrawalSenior Director, Product Management

Disclaimer

Today’s Speaker

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Sky is not the limit for data!Increase in Number of

CubeSat & Nanosatellites

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Data engineering—not new for NASA!

Curiosity Rover

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Data—making a difference?

Applications

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Let’s explore an aviation safety use case

Σ NODE

ψ

ψ

ψ

Radio

Alert

Junction1

2

3

Ranking

System

Layer 2

Layer 1: Parametric

Analysis

Layer 3: Heuristic

Analysis

To Air

Traffic Control

Sensor Pl Pd Pu Grp Priority Transmit

Pitch -50° 65° 50° 1 2 2

Roll -270° 15° 270° 1 3 3

Climb rate -35,000 ft/min 3,800 ft/min 3,500 ft/min 1 1 1

Altitude 3,000 ft 39,000 ft 43,100 ft 1 4 4

Cabin pressure n/a 6,500 ft 8,000 ft 2 4 5

Group sensor data

by sensor type

Sort sensor data

by priority

Search emergency

response database

Parametric bracket warning system Ranking system Heuristic system

Response

found?EXIT

Send emergency response

to ground control

YES

NO

Pl ≤ Pd ≤ Pu

Safe

operation

ALERT ALERT

Determine data

transmission priority

Send response to

automatic control

Sample parameters, group, priority, and transmission priority

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NASA’s Aviation Safety Reporting System

Aviation Safety

Reporting System

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Sample aviation safety use case—components

• IOT – Data Acquisition, standardization• Business Rules Validation• ML – Prediction & decision making• Transmission

• Data Ingestion• Data Quality – Cleansing, Standardization• Data Transformation/Business Rules• ML Integration• Reporting & Dashboards

• ML Model Creation• ML Model Feedback & improvement• Data Science Integration

Σ NODE

ψ

ψ

ψ

Radio

Alert

Junction1

2

3

Ranking

System

Layer 2

Layer 1: Parametric

Analysis

Layer 3: Heuristic

Analysis

To Air

Traffic Control

9 © Informatica. Proprietary and Confidential.9

Aviation safety use case demo flow

Red = Done outside Informatica mostly by developers

Blue = Done using Informatica products (EDC & Data Engineering Integration/Streaming)

Discover

Catalog Datasets

<Find the right datasetfor ML modeling>

Ingest

Find, Understand, Ingest Data

<Ingest the datain Realtime>

Prepare Data

Transform, Parse, Cleanse, Enrich Data

<Transform the sensor data, clean it and

prepare it for model>

Develop AI Model

Feature Engineering, Train, Fit, Validate,

Score & Select Model

Deploy Model

Production Data

Pipeline

<Deploy ML models

in the pipeline>

Consume

Monitor the health

of the model

Iterate and

refine model

Predictive Model Management

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Informatica Intelligent Data Platform

Sample aviation safety use case–using Informatica Intelligent Data Platform

Σ NODE

ψ

ψ

ψ

Radio

Alert

Junction 1

2

3

Ranking

System

Layer 2

Layer 1: Parametric

Analysis

Layer 3: Heuristic

Analysis

To Air

Traffic Control

DEI | Data Engineering Integration

DES | Data Engineering Streaming

EDP | Enterprise Data Preparation

EDS | Edge Data Streaming

DEIDES EDP

EDS

11 © Informatica. Proprietary and Confidential.11

w

End-to-end data management for AI & analytics

ANY

DATA

ANY

REGULATION

ANY

USER

ANY CLOUD / ANY TECHNOLOGY

ANY

LATENCY

METADATA

GOVERNANCE

INGEST STREAM INTEGRATE CLEANSE PREPARE DEFINE CATALOG RELATE PROTECT DELIVERENRICH

HYBRID

MODERN DATA INTEGRATION PATTERNS

2

100% Focus on Everything Data

VersatileCloud.

On-premises.

Big Data.

Best-in-Class

customersuccessservices

Modularand Integrated

Intelligent Data

Platform

Broadestecosystem

support

Globalpartner and

developer

network

Leaderin Enterprise

Cloud Data

Management

Proven Track

Record for over

25 Years

The Informatica Difference

Learn More

• Sign up for the free Informatica trials

https://www.informatica.com/trials.html

• Read more about Informatica AI/ML engine “CLAIRE”

https://www.informatica.com/about-us/claire.html

Thank You!