Why Open Data Science Matters | Gartner BI & Analytics Summit '16

© 2016 Continuum Analytics - Proprietary

WHY OPEN DATA SCIENCE MATTERS Why open source is eating the world

Travis Oliphant, CEO Michele Chambers, CMO & VP Products Continuum Analytics Gartner BI & Analytics Summit 2016

Agenda

© 2016 Continuum Analytics- Confidential & Proprietary

•  About Us •  What is Modern Analytics and how is different? •  Why does Open Data Science matter? •  Q&A

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© 2016 Continuum Analytics- Confidential & Proprietary 3

•  Travis Oliphant @teoliphant CEO & co-founder Continuum Analytics Ph.D. Mayo Clinic in Biomedical Engineering B.S., M.S. BYU Mathematics & Electrical Eng. Open Source contributor and leader since 1997

Creator of NumPy and SciPy Started Numba

Author Guide to NumPy

About Us


•  Michele Chambers @ mcAnalytics CMO & VP Product Continuum Analytics M.B.A Duke University, B.S. Computer Engineering Author

Big Data Big Analytics Wiley Modern Analytics Methodologies: Driving Business Value with Analytics Pearson FT Press Advanced Analytics Methodologies: Driving Business Value with Analytics Pearson FT Press

About Us

WHAT’S THE PROBLEM?


© 2016 Continuum Analytics - Confidential & Proprietary 6

Why are major corporations moving to Modern Analytics & Open Data Science?

Large Investment Banks Major Upstream Oil & Gas Global CPG Manufacturers How can I create and

deploy timely risk models? How can I possibly identify

the root causes of my complex problem and

remediate early enough to create revenue assurance?

How can I take advantage of all this new sensor

information now?


Industry Leaders Trusting Open Data Science

The Past vs. Present


Decreasing Use

•  Vendor lock in •  High costs •  Lack of integration •  Inability to easily deploy •  Skills gap

Proprietary Software

•  Avoids vendor lock in •  Reduces cost •  Open APIs and

connectors •  Eliminates chasm

between build & deploy •  Accessible to tomorrow’s

talent

Accelerating Adoption Open Source Software

Evolving Technology


•  Limited Data Sources •  Legacy Compute

Engines •  On-premise

Status Quo Proprietary Software

•  Big Data •  Modern Analytics •  Distributed Computing •  High Performance

Computing •  Cloud •  Streaming

Next Generation Open Source Software

Business Intelligence

How’s Modern Analytics Different from Traditional Analytics?


Traditional Analytics SQL

Analytics Descriptive Statistics

Data Mining

Predictive Analytics

Prescriptive Analytics Modern Analytics

Machine Learning

Simulation Optimization

How’s Modern Architectures Different from Traditional Architectures?


Distributed Modern Architecture

Cloud Computing

Parallel Computing

Parallel & Distributed Computing

Stream Computing

Monolithic Traditional Architecture

Centralized Computing

Network Computing

High Performance Computing

Evolving Roles


•  Statistician •  Programmer

Status Quo Proprietary Software

•  Data Science Teams •  Business Analyst •  Data Scientist •  Developer •  Data Engineer •  DevOps

Next Generation Open Source Software

How are Modern Roles Different from Traditional Roles?


Team | Collaborative Individual | Silo

Modern Roles Traditional Roles

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Modern Data Science Teams use…


Data Scientist •  Hadoop / Spark •  Programming

Languages •  Analytic Libraries •  IDE •  Notebooks •  Visualization

Biz Analyst •  Spreadsheets •  Visualization •  Notebooks •  Analytic

Development Environment

Data Engineer •  Database / Data

Warehouse •  ETL

Developer •  Programming


DevOps •  Database / Data

Warehouse •  Middleware •  Programming

Languages

RIGHT TECHNOLOGY FOR THE PROBLEM

Modern Data Science Teams Want


Collaboration

•  Iterate on analysis •  Share discoveries with team •  Interact with teams across

the globe

Interactivity

•  Interact with data •  Build high performance

models •  Visualize results in context

Integration

•  Work with open source and legacy data systems

•  Leverage data science languages: Python, R, Matlab, SAS, SPSS, Excel, Java, C/C++, C#, .NET, FORTRAN and more

Predict

Share

Deploy

with Open Data Science

WHAT’S OPEN DATA SCIENCE?


“ ”17

An interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms

Wikipedia

Data Science is …


Data Science is not just Machine Learning…


Distributed Systems


Machine Learning / Statistics

Web

Scientific Computing / HPC

Data Science is Interdisciplinary…


Hadoop, Spark

GPUs, mul2-‐cores

Classifica2on, deep learning

Regression, PCA

Web crawling, scraping, 3rd party data & API providers, predic2ve

services & APIs

Data warehouse, querying, repor2ng

Distributed Systems



Web


Open Data Science is …

an inclusive movement

that makes open source tools of data science -- data, analytics, & computation – easily work together as a connected ecosystem


Open Data Science Means Open….

Availability Innovation

Interoperability Transparency

For everyone in the data science team


OPEN DATA SCIENCE IS THE FOUNDATION TO MODERNIZATION

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Another words, if you want to…

Control the Chaos Empower the User Lead with Analytics Evangelize the New Modernize the Core


YOU’VE GOT TO USE OPEN DATA SCIENCE

Open Data Science Vibrant and Growing Community


Python Community

30M+ Anaconda Downloads

3M+

Packages in Anaconda

720+

R Community

16M+ Spark Python Usage

50%+


Open Data Science Community

A gathering of Python enthusiasts for sharing ideas and learning from each other for ever evolving challenges

Promotes and supports ongoing R&D of open source compu2ng tools through educa2onal, community and public channels

Support for the Apache Community of open source soJware projects which are for the public good

Suppor2ng the R community, the R Founda2on, and others developing and distribu2ng R

Open Source Communities Creates Powerful Technology for Data Science


Numba

dask

xlwings

Airflow

Blaze

Distributed Systems



Web


Python is the Common Language


Numba

dask

xlwings

Airflow

Blaze

Distributed Systems



Web



Python Trusted by Industry Leaders

“ ”28

Everyone at JPMorgan now needs to know Python and there are around 5,000 developers using it at Bank of America. There are close to 10 million lines of Python code in Quartz and we got close to 3,000 commits a day. It’s a good scripting language and easily integrated into both the front and back ends, which was one of the reasons we chose it in the first place.

Kirat Singh, Former Global Head of Risk Systems, Bank of America Merrill Lynch

Python is Everywhere



Why Companies are Migrating to ODS…

Large Investment Bank Major Upstream Oil & Gas Global CPG Manufacturer Problem •  Hard to find people to create

proprietary risk assessment models

•  Takes months and years to deploy Solution •  Moved to ODS and leveraged

innovation in ODS Results •  Create and deploy risk models in

days not years with easier to find and hire data scientists

Problem •  Complex model and simulation

required with disparate internal and external data

Solution •  Moved to ODS to easily integrate

multiple data feeds and leverage OS innovation

Results •  Created full lifecycle predictive

model and simulation for revenue assurance

Problem •  Unable to ingest Big Data from

sensors to proactively monitor oil well holes

Solution •  Moved to ODS and leveraged

diversity of ODS analytics to create novel visualizations and predictive models using sensor data

Results •  Gained insights into oil hole issues

in weeks not years to detect issues earlier and increase profitability

Python’s Not the Only One…


SQL

Distributed Systems



Web


But it’s also a Great Glue Language


SQL

Distributed Systems



Web


Anaconda is the Open Data Science Platform Bringing Technology Together…


Numba

dask Airflow

SQL

xlwings Blaze

Distributed Systems



Web



But Most Importantly Empowering Everyone on the Data Science Team

Data Scientist Biz Analyst Data Engineer Developer DevOps

Deploy & Operate

Explore & Analyze

Collaborate & Publish

•  Accelerates Time-to-Value

•  Empowers the Data Science team

•  Connects Open Source Communities

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is…. the leading modern open source analytics platform powered by Python the fastest growing open data science language

the innovative open data science platform to exploit data, analytics, and computation


Introducing Anaconda The Modern Open Source Analytics Platform Powered by Python

§  Enterprise Ready PlaNorm –  Simplify administra2on –  Use modern data science

–  Collaborate with en2re team –  Leverage modern architectures

–  Integrate data sources –  Accelerate performance Security

Governance

Provenance

R Scala

Python

R | Scala

JS

C | C++ Fortran

APPLICATIONS

DATA

HARDWARE

ANALYTICS

Model Building

Data Exploration Software Development

HIGH PERFORMANCE

Business Analyst

Data Scientist

Developer

Data Engineer

DevOps

Data Science Team

Cloud On-premises

LANGUAGES

OPERATIONS

ANACONDA GIVES SUPERPOWERS TO PEOPLE WHO CHANGE THE WORLD


Modern Data Science Teams Love Anaconda


Data Scientist •  Hadoop / Spark •  Programming

Languages •  Analytic Libraries •  Notebooks •  Visualization •  IDE

Biz Analyst •  Spreadsheets •  Visualization •  Notebooks •  Analytic

Development Environment

Data Engineer •  Database / Data

Warehouse •  ETL

Developer •  Programming


DevOps •  Database / Data

Warehouse •  Middleware •  Programming

Languages


Anaconda Trusted by Industry Leaders Financial Services

Risk Mgmt, Quant modeling, Data exploration and processing, algorithmic trading, compliance reporting

Government Fraud detection, data crawling, web & cyber data analytics, statistical modeling

Healthcare & Life Sciences Genomics data processing, cancer research, natural language processing for health data science

High Tech Customer behavior, recommendations, ad bidding, retargeting, social media analytics

Retail & CPG Engineering simulation, supply chain modeling, scientific analysis

Oil & Gas Pipeline monitoring, noise logging, seismic data processing, geophysics

Questions?

… and so that is why Open Data Science is eating the world.


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Why Open Data Science Matters | Gartner BI & Analytics Summit '16