the future of bi - snowflake inc. · 2019-12-01 · bi must evolve to work within in these new...

© 2019 Snowflake Inc. All Rights Reserved

THE FUTURE OF BI

JAMIE DAVIDSON

VP PRODUCT

LOOKER


>1800

CustomersSigned agreement to be

acquired by GCP as part of multi-cloud strategy

>800

Employees

GlobalSanta Cruz, San

Francisco, Dublin, London, New York,

Boulder, Chicago, Tokyo

PartnersSnowflake, Amazon,

Cloudera, Microsoft,

HPE, IBM

>50Supported SQL dialects


LOOKER AT A GLANCE


OUR MISSION:TO EMPOWER PEOPLE

THROUGH THE SMARTER USE OF

DATA

eCommerce &

MarketplacesFinanceTechnology RetailMedia

RESONATES WITH CUSTOMERS ACROSS THE SPECTRUM


THE BI MARKET IS

CHANGING


3 EMERGING TRENDS IN BUSINESS INTELLIGENCE

6

1 2 3

Everyone

needs data.

Everyone.

Proliferation

of SaaS apps.

Infrastructure

has evolved.


TREND #1

EVERYONE NEEDS

DATA… EVERYONE


WE EXPECT DATA WHEN WE SHOP

8


WE EXPECT DATA WHEN WE CHILL

9


NO SURPRISE! THE DATA-HUNGRY WORKFORCE HAS ARRIVED

10

Growth

Hacker

Quantitative

Marketer

Data Driven

Product

Manager

Sales &

Revenue Ops

Analyst

DevOps

Engineer

Customer

Success

Manager


TREND #2

PROLIFERATION OF

SaaS APPLICATIONS


SaaS APPS ARE GROWING LIKE CRAZY

12

The average

enterprise uses

1,100+ SaaS apps

to run their business


BETWEEN 2018 TO 2023,

500 MILLION NEW BUSINESS APPS

WILL BE CREATED

13

IDC: FutureScape: Multiplied Innovation Takes Off, Powered by AI, Distributed Public Cloud, Microservices,

Developer Population Explosion, Greater Specialization and Verticalization, and Scaling Trust


TRADITIONAL DATA WRANGLING APPROACHES DON’T WORK

14

3,000+

Workbooks

1,000+

SQL Snippets

1,500+

New ad-hoc requesters

50,000+

Lines ofETL code


HOW CAN WE CREATE A DATA

PLATFORM THAT CAN SERVE OUR

WHOLE ORGANIZATION?

(And doesn’t take 1,000s of data experts and a zillion

lines of brittle ETL scripts to build and maintain)


THERE IS HOPE!


TREND #3

DATA INFRASTRUCTURE

HAS EVOLVED


DATA ENGINEERING TRENDS PROVIDE HOPERemoving constraints on data and analytics

18

Databases are bigger

faster cheaper

ELT is

simpler and iterative

SQLremains the

standard

SUMMARY

TRADITIONAL PIPELINE APPROACH

Extracts and Cubes

INFLEXIBLE

Data Warehouses

SLOW

Questions, Agility, Distribution

LIMITED

A

P

HEAVYWEIGHT

Transformation

BUSINESS USERBI TEAMETL TEAM DBAs

WHY IT HAPPENED

HAVE A NEW QUESTION?

RAWDATA

COLLECTIONWHAT

HAPPENED

MODERN ELT PIPELINE

Unrestricted Questions

FLEXIBLESIMPLE

Extract + Load

A

P

U W

XU

A

MODERN MPP DATASTORE

RAWDATA

COLLECTION

DATA ENGINEERS BUSINESS USERS

SQL

Semantic Model +“Magic”

AGILE

SOFTWARE ITERATION

A COMPLETE DATA PICTURE

Transform on Query

PERFORMANT


SO…

WHAT IS THE FUTURE

OF BUSINESS

INTELLIGENCE?


GUIDING PRINCIPLES FOR THE FUTURE

22

Data-Driven Workforce:

Everyone gets better at their job

with data. We must supply actionableinsights when &

where people need them.

Rise of SaaS Applications

Growth of the app ecosystem is accelerating. BI must evolve

to work within in these new

experiences.

Modern Data Warehouse

Modern cloud databases will

continue to provide massive gains in cost, size, speed,

analytics.


THE LOOKER DATA ANALYTICS PLATFORM

23

Any SQL Database

SaaS Apps

Business Planning

Web Analytics

Business Intelligence

Self-ServeExploration

Visualization Export SDK iFrame Javascript

Business Operations and Workflows

Email Actions S3 API

API for DataGit Version

ControlJDBC

Connections

User Management & Security

Transactional DBs

Shared Data Foundation

Governance & Unified Metrics

Data Experiences

Total Flexibility

Embedding and Customization

Robust Analytics and Alerting


DIFFERENCES OF THE LOOKER DATA PLATFORM

24

100% In-Database

Radically simplifies DataOps

Leverage modern data

warehouse technologies

Business users discover

insights on the entire data set

Data federation and

virtualization

110% API coverage

Every query and visualization is

addressable by URL

Simple extensibility and

connectivity to web services

Applications and Workflow

Integrations

Extensible Web Architecture

Build data-driven apps

Flexible Modeling Layer

Single source of truth

Store and manage all business

definitions in one central location

Looker intelligently reads

relationships between tables in

your database

Enables business users to access

and build on complex datasets


Yapstone Demonstration

ANIL KUMAR PULI

SR. DATA ENGINEERING MANAGER

YAPSTONE

PRAVIN DARBARE

SR. DIRECTOR OF DATA SYSTEMS

YAPSTONE

PROPRIETARY AND CONFIDENTIAL

Global Marketplaces Large Vertical Markets

Millions of

Unknown

Consumers

Millions of

Unknown

Merchants

$ $

Vacation

Rental

$200B

Rent

$500B

New

Verticals

$TN

26

PROPRIETARY AND CONFIDENTIAL

27

Customer Journey ->

Onboarding Contract

to Cash

Pay-In

Pay-OutChargebacks

Refunds

Recaptures

Bouncebacks

Collections

Revenue

Operating

Expenses

Write-off

▪ Supporting Reports▪ Marketing Campaigns

Onboarding Contract to cash Transaction Risk/Chargeback Recap/BB/Coll RevenueCustomer Journey

KPI1 KPI2 KPI3 KPI4 KPI5 KPI6

PROPRIETARY AND CONFIDENTIAL 28

• Executive level KPIs

• Portfolio performance

• Revenue tracking & alerts

• Leads, opportunities, contracts etc.

Visibility on Yapstone Business KPIs

• New product/feature performance monitoring

• Product gaps, issues & improvements

• Revenue forecasting vs. actual

Product/Feature Performance Management

• Stage onboarding –

• Faster Seller onboarding

• Seller Retention – stickiness

• Fraud management

Data Driven Decisions

• PAAS – “Platform As A Service”

• DAAS – “Data As A Service”

PAAS and DAAS

• Reporting Portal

• Linked Analysis

• Fraud Protection

Data Products


Data Integration Data Platform “Data as a Service”

AWS | Recon Framework | Monitoring Framework | Link Analysis | Artificial Intelligence | Machine Learning

Data

In

ge

sti

on

/ I

nte

gra

tio

n

Clo

ud

So

urc

es

Ya

ps

ton

e S

ou

rce

s

Finance

Opportunity/Leads

Customer Service

Cloud Contact - Call

Invoice, Funds-in/out,

Refunds, Chargebacks

Staged Onboarding

Beneficial Ownership

Standalone Payouts

HA Payouts

Snowflake Cloud

Em

bed

ded

An

aly

tics

Cu

sto

mer

Serv

ice

Cloud


• 25+ complex data integrations

• Internal/Third party cloud data source integrations

• Near Real time data integration with Couchbase

• Data Lake and Visualization

Yapstone Data Platform• Linked Analysis using advance graph databases

• Looker Bot for internal/external customer engagement

• Virtual Reality for reporting

• Voice recognition for training and demonstrations

• Machine learning for Risk/Forecasting/Payments use

case

Innovation

• Product

• Finance/Accounting

• Risk

• Legal/Compliance

• Chargebacks/Collections Teams

• Account Relationship Management

• External Customers

Stakeholder Engagement• Embedded analytics

• Reporting APIs

• Visibility on fraudulent transactions and patterns

• Data reconciliation framework

• Advance Search to identify critical events

Advance Capabilities

Internal/External Customers Technology PartnersData Driven Ecosystem Data Nerd Community


Embedded Analytics

• Embedding Looker Dashboards

• Data Visualizations by making API call to Look

Self Service – Data Discovery

• Ad-Hoc analysis capabilities

• Slice and Dice data using LookML Model

Advance Features

• Navigation to other cloud systems like Zendesk, Salesforce etc. from dashboards

• Custom filters/Tooltips/Visualizations

• Advance Search


Thank YouLearn more about us at Looker.com

the future of bi - snowflake inc. · 2019-12-01 · bi must evolve to work within in these new...

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