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Top Trends for Hadoop in 2015March 4, 2015


Top Trends in Hadoop for 2015 - Forrester

Big Data Trends - Hortonworks

High performance analytics at scale in Hadoop - Actian

Agenda


John Kreisa

Vice President, Strategic Marketing

Hortonworks

Mike Gualtieri

Principal AnalystForrester

Presenters

Christy Maver

Global Product Marketing Director

Actian

Hadoop Trends And The Future Of AnalyticsMike Gualtieri, Principal Analyst

March 4, 2015

© 2015 Forrester Research, Inc. Reproduction Prohibited 5

7%

16%

15%

18%

20%

24%

5%

12%

18%

17%

16%

33%

Social related projects

Mobile related projects

Cloud related projects

Systems of engagementapplications

Systems of record applications

Data related projects

2nd PriorityTop Priority

Please rank the following technologies according to their importance and investment within your firm?

Executives and technology decision-makers are remembering the power of data.

Why?

Meet business demand for analytics of all kinds.


What are the main business and technical requirements or inadequacies of earlier-generation business intelligence technologies that lead you to consider new BI techniques and technologies?

Base: 452 North American technology decision-makersRespondents answering “don’t know” are not shownSource: Global Data and Analytics Survey, 2014

Base: 249 North American business decision-makersRespondents answering “don’t know” are not shownSource: Global Data and Analytics Survey, 2014

Most want deeper insights through advanced analytics but familar challenges persist.

2%

16%

20%

28%

29%

31%

32%

32%

34%

35%

45%

2%

12%

14%

26%

23%

35%

28%

31%

27%

33%

44%

Other (please specify)

Earlier-generation technology is too expensive

The velocity of data is too high for earlier technologies

The number of data formats that we must be able to deal with exceedsour ability to cost-effectively integrate

Analysis requirements change too fast to keep up with

The performance of certain analysis is not sufficient

We don't know what our entire data universe contains, we need new waysto explore data and discover patterns and insights

We want to access data that was not accessible for us with existingtechnologies

Data changes or becomes available much faster than we can process insupport of business decisions

Data volumes have grown beyond what we can cost-effectively manage

We want deeper insights through advanced analytics

Business decision makersTechnology decision makers


Growth and customer experience are priorities to business leaders


#Royalty


Trend

Consumers want to be treated like royalty.


Royalty experiences have contextual

awareness and adapt to serve a single consumer.


Treat consumers like royalty to get their loyalty.

Behavior

AttributesActivities

Relationships

Content Usage

Social

LikesDevices

Me


#Analytics


Businesses often think of analytics as a set of historical reports and dashboards…


…but, analytics is also about the future.


It’s important to have all kinds of analytics.

Past Present Future

Learn React Anticipate

Predictive Analytics

Real-time Analytics

Descriptive Analytics

(Traditional Analytics)

ANALYTICS

UBIQUITOUSInformation-driven business culture that uses completely available analytics of all kinds to continuously improve customer experience, operations efficiency, and decision-making.


What percentage of enterprise data do firms use for analytics?

A. 12%B. 34%C. 53%D. 76%

EnterpriseData

Quiz


#Hadoop


Gather all your data and do it cost effectively.

Data


Analyze the heck out of data - every which way.

Process


#DataOS


Hadoop adoption is not an option.


#EveryIndustry


Every industry is graced with more data…

› Richer transactional data from portfolio of dozens or hundreds of business applications

› Usage and behavior data from web and mobile apps

› Social media data

› Sensor and event data from IoT devices

› Data economy – firms buying and selling data

› Derived data from analytics


Financial Use Case

How can you prevent this dude from fleecing you?


Financial Services Use Case

What are movers and shakers saying about equities that we cover?


How can you listen to customers to measure share of voice, efficacy, and side effects?

HealthcareUse Case


How can you know if your baby is sleeping soundly or if something is wrong?

HealthcareUse Case


What if you knew your customer was near your store on a sunny day?

Retail Use Case


How can show an ad that this household will find relevant?

Retail Use Case


#Trends

TRENDS


1100

1001

1011

001

0100

1001

1011

001

0100

1100

1101

101

0100

1001

10

1. Hadooponomics make enterprise adoption mandatory.

Hadoop is an enterprise

priority for 2015.

TRENDS


2. SQL becomes Hadoop’s killer app for 2015.

SQL must be blazing fast, ANSI-compliant, and

optimized for Hadoop.

SELECT sum(S.commission) FROM Customers C, Salesperson SWHERE C.prodName = “SQL Edition’ AND S.salesperson = “You”

TRENDS


3. Enterprise software vendors close Hadoop’s data management and governance gaps.

Ubiquitous analytics requires an industrialized, end-to-end

analytics platform for whereever data lives..

TRENDS


4. The Hadoop skills shortage disappears.


Predictive analytics tools reduce need for data scientists.

Analytics platform operationalizes analytics faster.

SQL is a ubiquitous

skill.

TRENDS


5. Enterprises will let thousands of Hadoop clusters bloom in the cloud.

Data often originates in the cloud.

TRENDS


6. Hadoop won’t just be for analytics anymore.

Applications must embed applications to be more personal

and contextual.

TRENDS


7. The Hadoop ecosystem standardizes.

Next prediction.

Enterprises need a portable set of

Hadoop services.


#Opportunity


Your customers’ customers’ are ready


Get ready1. Walk through critical or challenging business processes

- At each step of the business process ask how analytics could improve the process

2. Walk through customer journey to improve customer experience

- At each step of the customer journey, ask how analytics could improve the customer experience


#2015

Thank youMike [email protected]


Traditional systems under pressure

Challenges• Constrains data to app• Can’t manage new data

• Costly to Scale

Business Value

Clickstream

Geolocation

Web Data

Internet of Things

Docs, emails

Server logs

20122.8 Zettabytes

202040 Zettabytes

LAGGARDS

INDUSTRY LEADERS

1

2 New Data

ERPCRM

SCM

New

Traditional


Hadoop emerged as foundation of new data architecture

Apache Hadoop is an open source data platform for managing large volumes of high velocity and variety of data• Built by Yahoo! to be the heartbeat of its ad & search business

• Donated to Apache Software Foundation in 2005 with rapid adoption by large web properties & early adopter enterprises

• Incredibly disruptive to current platform economics

Traditional Hadoop AdvantagesManages new data

paradigmHandles data at scaleCost effectiveOpen source

Application

StorageHDFS

Batch ProcessingMapReduce


OPERATIONAL TOOLS

DEV & DATA TOOLS

INFRASTRUCTURE

Hadoop is deeply integrated in the data centerSO

UR

CES

EXISTING Systems

Clickstream Web &Social Geolocation Sensor & Machine

Server Logs Unstructured

DA

TA S

YSTE

M

RDBMS EDW MPP

HANA

APPL

ICAT

ION

S

BusinessObjects BI

Deep PartnershipsHortonworks engages in deep engineered relationships with the leaders in the data center, such as HP, Microsoft, Redhat, SAP, SAS & Teradata

Broad PartnershipsOver 600 partners work with us to certify their applications to work with Hadoop so they can extend big data to their users

HDP 2.1

Gov

erna

nce

& In

tegr

atio

n

Secu

rity

Ope

ratio

nsData Access

Data Management

YARN


Actian and the Modern Data Architecture

Modern Data Architecture

• Enable applications to have access to all your enterprise data through an efficient centralized platform

• Supported with a centralized approach governance, security and operations

• Versatile to handle any applications and datasets no matter the size or type

Actian Extends Hadoop’s Reach

• Unleashing SQL resources on Hadoop increases value to customers

• Actian’s Native YARN offering excels at meeting market demand for SQL

• Actian tools help to move POC to Production

Clickstream Web & Social

Geolocation Sensor & Machine

Server Logs

Unstructured

SOU

RC

ES

Existing SystemsERP CRM SC

M

ANAL

YTIC

S

Data Marts

Business Analytics

Visualization& Dashboards

ANAL

YTIC

S

Applications Business Analytics


°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

HDFS (Hadoop Distributed File System)

YARN: Data Operating System

Interactive Real-TimeBatch Partner ISVBatch BatchMPP

EDW


Hadoop Driver: Cost optimization

• Archive Data off EDWMove rarely used data to Hadoop as active archive, store more data longer

• Offload costly ETL processFree your EDW to perform high-value functions like analytics & operations, not ETL

• Enrich the value of your EDWUse Hadoop to refine new data sources, such as web and machine data for new analytical context

ANAL

YTIC

S

Data Marts

Business Analytics


HDP helps you reduce costs and optimize the value associated with your EDW

ANAL

YTIC

SD

ATA

SYS

TEM

S

Data Marts

Business Analytics


HDP 2.2

ELT°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

°

N

Cold Data, Deeper Archive& New Sources

Enterprise Data Warehouse

Hot

MPP

In-Memory

Clickstream Web & Social

Geolocation Sensor & Machine

Server Logs

Unstructured

Existing SystemsERP CRM SC

MSOU

RC

ES


Single ViewImprove acquisition and retention

Predictive Analytics Identify your next best action

Data DiscoveryUncover new findings

Financial Services

New Account Risk Screens Trading Risk Insurance Underwriting

Improved Customer Service Insurance Underwriting Aggregate Banking Data as a Service

Cross-sell & Upsell of Financial Products Risk Analysis for Usage-Based Car Insurance Identify Claims Errors for Reimbursement

TelecomUnified Household View of the Customer Searchable Data for NPTB Recommendations Protect Customer Data from Employee Misuse

Analyze Call Center Contacts Records Network Infrastructure Capacity Planning Call Detail Records (CDR) Analysis

Inferred Demographics for Improved Targeting Proactive Maintenance on Transmission Equipment Tiered Service for High-Value Customers

Retail360° View of the Customer Supply Chain Optimization Website Optimization for Path to Purchase

Localized, Personalized Promotions A/B Testing for Online Advertisements Data-Driven Pricing, improved loyalty programs

Customer Segmentation Personalized, Real-time Offers In-Store Shopper Behavior

ManufacturingSupply Chain and Logistics Optimize Warehouse Inventory Levels Product Insight from Electronic Usage Data

Assembly Line Quality Assurance Proactive Equipment Maintenance Crowdsource Quality Assurance

Single View of a Product Throughout Lifecycle Connected Car Data for Ongoing Innovation Improve Manufacturing Yields

HealthcareElectronic Medical Records Monitor Patient Vitals in Real-Time Use Genomic Data in Medical Trials

Improving Lifelong Care for Epilepsy Rapid Stroke Detection and Intervention Monitor Medical Supply Chain to Reduce Waste

Reduce Patient Re-Admittance Rates Video Analysis for Surgical Decision Support Healthcare Analytics as a Service

Oil & GasUnify Exploration & Production Data Monitor Rig Safety in Real-Time Geographic exploration

DCA to Slow Well Declines Curves Proactive Maintenance for Oil Field Equipment Define Operational Set Points for Wells

GovernmentSingle View of Entity CBM & Autonomic Logistic Analysis Sentiment Analysis on Program Effectiveness

Prevent Fraud, Waste and Abuse Proactive Maintenance for Public Infrastructure Meet Deadlines for Government Reporting

Hadoop Driver: Advanced analytic applications


Hadoop Driver: Enabling the data lake

• Data Lake Definition

• Centralized ArchitectureMultiple applications on a shared data set with consistent levels of service

• Any App, Any DataMultiple applications accessing all data affording new insights and opportunities.

• Unlocks ‘Systems of Insight’Advanced algorithms and applications used to derive new value and optimize existing value.

SCAL

E

SCOPE

Drivers:1. Cost Optimization2. Advanced Analytic Apps

Goal:• Centralized Architecture• Data-driven Business

DATA LAKE

Journey to the Data Lake with Hadoop

Systems of Insight


Case Study: 12 month Hadoop evolution at TrueCarD

ata

Plat

form

Cap

abili

ties

12 months execution plan

June 2013Begin Hadoop Execution

July 2013Hortonworks Partnership

May ‘14IPO

Aug 2013Training & DevBegins

Nov 2013Production Cluster60 Nodes2 PB

Jan 201440% DevStaff Perficient

Dec 2013Three Production Apps(3 total)

Feb 2014Three More Production Apps(6 total)

12 Month Results at TRUECar• Six Production Hadoop Applications• Sixty nodes/2PB data• Storage Costs/Compute Costs

from $19/GB to $0.23/GB

“We addressed our data platform capabilities strategically as a pre-cursor to IPO.”


Next Steps…

• Download the Hortonworks SandboxLearn Hadoop

Build Your Analytic App

Try Hadoop 2

More about Actian & Hortonworkshttp://hortonworks.com/partner/Actian/

Contact us: [email protected]


High performance analytics at scale in Hadoop

Christy Maver, Global Product Marketing Director, Actian


What to look for in a SQL in Hadoop Platform

• Collaborative architecture• Open access to Actian

formats• Support for non-Actian

formats

No vendor lock-in

• Fastest data prep and ingestion

• Fastest analytic engines• Unbridled processing

power on data nodes in a Hadoop cluster

• Full SQL support• Extreme scalability• Full security• High Availability &

Disaster Recovery

Results you need when you need them

Proven technology advantages

Open Fast Enterprise-Grade


Actian Vortex – High Performance Analytics at Scale in Hadoop


Fully ACID compliant – Get transactional integrity in Hadoop to prevent inaccurate results

What Sets Actian Vortex Apart from other SQL on Hadoop offerings?

Full ANSI SQL 92 support – You can use of ALL standard BI tools and apps

Native DBMS Security – Gain authentication, user and role-based security, data protection, and encryption

Open APIs – Your third-party ecosystem can gain read access to our block format

Highly Performant – Get answers up to 30x faster than possible with another offering

Mature, proven planner and fastest optimizer – Maximize number of nodes, CPU, memory and cacheHadoop distribution agnostic – Avoid vendor

lock-in

Native in-Hadoop YARN – Manage Hadoop resources automatically to prevent inefficiencies

Collaborative architecture - Query native Hadoop file formats (like Parquet) without ingestion

Update Capability – Update Hadoop data without impacting read performance

Highest Concurrency – Deploy simultaneous users and tasks without long wait times


Questions And Answers


Learn more

• Download Actian Vortex Express:

• Actian is joining the Hortonworks Roadshow – find out more:

o http://www.actian.com/resources/#UpcomingEventsbrWebinars

• Additional questions? Contact us at [email protected]

Bigdata.actian.com/sql-in-hadoop

http://www.actian.com/resources/%23UpcomingEventsbrWebinars