New Enterprise Associates, Andreessen Horowitz, Accel Partners, Intel Capital and Khosla Ventures are the top 5 investors in big data analytics, with over 10 investments each.
Tracxn Startup Research: Data as a Service Landscape, August 2016Tracxn
The top three funded sub-sectors till date are market intelligence (149 investments, $1.3B), financial data providers (158 investments, $1.2B), and geospatial data providers.
Tracxn Research — Big Data Infrastructure Landscape, September 2016Tracxn
Following a rather muted 2015, the year 2016 witnessed an impressive bounce back by the big data sector, with a total funding of $1.1B secured in 37 rounds.
Tracxn Research - Energy Storage Landscape, August 2016Tracxn
There have been six acquisitions in this space in 2016 - the largest disclosed deal among them was in May, when Saft Batteries was acquired by Total for $1.1B.
Tracxn Research: Energy Efficiency Landscape, August 2016Tracxn
Lighting Products (Cree, Bridgelux), and BEMS (Building energy management systems) (Synapsense, First Fuel) are two sectors in energy efficiency to have seen over a billion dollars in investments.
Tracxn Research — Business Intelligence Landscape, September 2016Tracxn
Tracxn's Business Intelligence 2016 report covers companies that develop and provide Business Intelligence (BI) & Analytics software. It also covers prominent industry specific BI solutions.
Tracxn Startup Research: Data as a Service Landscape, August 2016Tracxn
The top three funded sub-sectors till date are market intelligence (149 investments, $1.3B), financial data providers (158 investments, $1.2B), and geospatial data providers.
Tracxn Research — Big Data Infrastructure Landscape, September 2016Tracxn
Following a rather muted 2015, the year 2016 witnessed an impressive bounce back by the big data sector, with a total funding of $1.1B secured in 37 rounds.
Tracxn Research - Energy Storage Landscape, August 2016Tracxn
There have been six acquisitions in this space in 2016 - the largest disclosed deal among them was in May, when Saft Batteries was acquired by Total for $1.1B.
Tracxn Research: Energy Efficiency Landscape, August 2016Tracxn
Lighting Products (Cree, Bridgelux), and BEMS (Building energy management systems) (Synapsense, First Fuel) are two sectors in energy efficiency to have seen over a billion dollars in investments.
Tracxn Research — Business Intelligence Landscape, September 2016Tracxn
Tracxn's Business Intelligence 2016 report covers companies that develop and provide Business Intelligence (BI) & Analytics software. It also covers prominent industry specific BI solutions.
Tracxn Research — Ecommerce Enablers Landscape, November 2016Tracxn
The total M&A activity in the year to date was valued at more than $8.5B (excluding undisclosed acquisitions), while total investments were valued at $921M.
Tracxn Insurance Tech Landscape June 2016 ReportTracxn
Business models like Internet first insurers, enablers, distribution platforms, and P2P insurance, all have seen an uptick in number of companies founded.
Tracxn Research — Mobile Dev Tools Landscape, November 2016Tracxn
$747M has been invested in the mobile devtools space in 2015/16, with investments in MADP (mobile application development platforms, $128M), and app prototyping ($56M) startups peaking this year.
Tracxn Research — Marketing Tech Landscape, September 2016Tracxn
The report covers companies that provide tools for marketers to create, manage and analyse their marketing campaigns across multiple channels ranging from email and social media to mobile.
Tracxn Wind Energy Landscape Report July 2016Tracxn
The top business models are built around power generation (Greenko Group, ReNew Power Ventures), manufacturing (Clipper Wind, Suzlon), and service providers (SITAC Renewable energy, PNE Wind).
Tracxn Research: Enterprise Collaboration Landscape, August 2016Tracxn
File synchronisation and sharing (Box, Dropbox), conferencing (BlueJeans Network, Fuze), and messaging and chat room (Slack, Symphony) are the top three business models, each having seen over a billion dollars in investments.
Tracxn Research — Immuno-Oncology Landscape, September 2016Tracxn
In 2015/16, five startups in this space — Stemcentrx, Gritstone Oncology, Hengrui Therapeutics, and Zai Lab secured big ticket funding rounds of $100 million and above.
Tracxn Research — Enterprise Collaboration Landscape, November 2016Tracxn
Investments in the year to date rose by 10% YoY, to $1.1B, as the enterprise collaboration space goes through a shift from a document centric to a conversational model.
Tracxn Research: Solar Energy Startup Landscape, September 2016Tracxn
Tracxn’s Solar Energy Landscape report covers manufacturers of solar wafers and solar modules, solar based heating, charging and lighting solutions, and other services related to the generation of solar power.
Tracxn Research - Event Management Landscape, January 2017Tracxn
Local event discovery platforms secured 90% of the total funding. 2016 marked a sector peak for this sector in term of total funding. The sector also witnessed 20 acquisition deals.
Tracxn Research — Ecommerce Enablers Landscape, November 2016Tracxn
The total M&A activity in the year to date was valued at more than $8.5B (excluding undisclosed acquisitions), while total investments were valued at $921M.
Tracxn Insurance Tech Landscape June 2016 ReportTracxn
Business models like Internet first insurers, enablers, distribution platforms, and P2P insurance, all have seen an uptick in number of companies founded.
Tracxn Research — Mobile Dev Tools Landscape, November 2016Tracxn
$747M has been invested in the mobile devtools space in 2015/16, with investments in MADP (mobile application development platforms, $128M), and app prototyping ($56M) startups peaking this year.
Tracxn Research — Marketing Tech Landscape, September 2016Tracxn
The report covers companies that provide tools for marketers to create, manage and analyse their marketing campaigns across multiple channels ranging from email and social media to mobile.
Tracxn Wind Energy Landscape Report July 2016Tracxn
The top business models are built around power generation (Greenko Group, ReNew Power Ventures), manufacturing (Clipper Wind, Suzlon), and service providers (SITAC Renewable energy, PNE Wind).
Tracxn Research: Enterprise Collaboration Landscape, August 2016Tracxn
File synchronisation and sharing (Box, Dropbox), conferencing (BlueJeans Network, Fuze), and messaging and chat room (Slack, Symphony) are the top three business models, each having seen over a billion dollars in investments.
Tracxn Research — Immuno-Oncology Landscape, September 2016Tracxn
In 2015/16, five startups in this space — Stemcentrx, Gritstone Oncology, Hengrui Therapeutics, and Zai Lab secured big ticket funding rounds of $100 million and above.
Tracxn Research — Enterprise Collaboration Landscape, November 2016Tracxn
Investments in the year to date rose by 10% YoY, to $1.1B, as the enterprise collaboration space goes through a shift from a document centric to a conversational model.
Tracxn Research: Solar Energy Startup Landscape, September 2016Tracxn
Tracxn’s Solar Energy Landscape report covers manufacturers of solar wafers and solar modules, solar based heating, charging and lighting solutions, and other services related to the generation of solar power.
Tracxn Research - Event Management Landscape, January 2017Tracxn
Local event discovery platforms secured 90% of the total funding. 2016 marked a sector peak for this sector in term of total funding. The sector also witnessed 20 acquisition deals.
Tracxn Research — Insurance Tech Landscape, October 2016Tracxn
Our insurance tech report features an exhaustive Q&A with Patrick Kershaw and John Massey, Managing Partners at Leo Tech, and Andrea Traversone, Partner at Amadeus Capital Partners, who share their perspectives on market trends, investment outlook, areas of disruption, and more.
Tracxn Research — Enterprise Storage Landscape, November 2016Tracxn
Startups which offer backup storage solutions for enterprises emerged as the top funded business model of the year in the enterprise storage sector, accounting for 40% ($371M) of the total funding secured by the sector. The backup storage business model also witnessed a 70% YoY rise.
Tracxn Research: Enterprise Security Landscape, August 2016Tracxn
Network security, endpoint security, and BYOD security are the top three funded business models in the enterprise security sector, in which 10 business models have attracted $1B+ investments.
Tracxn Research — Investment Tech Landscape, October 2016Tracxn
A number of Asian companies are among top funded in the last one year - Guangzhou-based Zhiniu8 ($150M, Series C), Singapore-based M-DAQ ($95M, Series C), Beijing-based Jusfoun Big Data ($76M, Series C), and Shanghai-based Madai Licai ($65M, PE) accounted for the top investments in the last year.
Mobile Marketing is one of 50+ sectors we track for finding highly investable startups for venture capital funds. In here, we have tracked startups across various segments like Attribution, Mobile Retargeting, Mobile Video, Native Ads, Real Time Bidding (RTB) and many more.
This sector has seen a lot of investment activity lately. The companies funded in just the last 12 months include (with total funding $): Millenial Media ($240M), Epom ($7M ), MetaMarkets ($28.5M), AppsFlyer ($7.1M ), TapStream ($700K ), TapAd (15.3M), Appier ($6M ), BlueCava ($39M ), Crosswise ($2M ), URX ($15.1M ), PlaceIQ ($27M ), Adtile ($7.2M), AdsNative ($1.5M ), Sharethrough ($28M ), Kiip ($15.4M ), MediaSpike ($5.2M ), Mnectar ($7M ), Voxel ($1.6M ), PushSpring ($1.5M),SilverPush ($1.6M ), TapCommerce ($10M ), ActionX ($5M ), Smaato ($43M), Adtheorent ($4M ), Inneractive ($14M ), Flurry ($73.3M), StrikeAd ($10.2M ), Apsalar ($14.8M ), RunAds ($1.5M ), Vungle ($25.5M )
BootstrapLabs - Tracxn Report - artificial intelligence for the Applied Arti...BootstrapLabs
This report covers companies that provide the infrastructure for creating Artificial Intelligence. These Infrastructure companies include those working on Machine Learning, Deep Learning based platforms, libraries. Some of theses companies also provide platforms for Natural Language Processing and Visual Recognition. In the Applications section, the report covers companies leveraging AI techniques to build applications tailored for end use in Enterprise, Industry & Consumer sectors.
Over $1B has been invested in AI-Infrastructure startups since 2010 with ¬$340M being invested in 2015. Over $7.5B has been invested in AI-Applications startups since 2010 with $2.3B being invested in 2015.
Tracxn Research — Artificial Intelligence Startup Landscape, September 2016Tracxn
Notable investments in 2016 include antivirus and endpoint protection vendor Cylance ($100M Series D), Digital Reasoning ($40M, Series D), and Globality, ($27M, Series B).
Tracxn Research — Business Intelligence Landscape, December 2016Tracxn
Despite a YoY decline in seed and early stage rounds and capital invested, 2016 was the fourth consecutive year in which the sector witnessed $1B+ plus investments.
Evolution of Data Analytics: the past, the present and the futureVarun Nemmani
This paper delves into the topic of advanced analytics, the current industry demands to utilize and analyze huge/diverse amounts of data, how big data analytics is becoming a part of the decision making process and to anticipate trends. This paper takes the reader from Analytics era 1.0 to the current Analytics era 3.0; shows the future projections of big data analytics and also the current leaders of the Big Data Analytics market.
As 2017 begins, we are seeing big data and data science communities engage with new tools that specifically cater to data scientists and data engineers who aren’t necessarily experts in these techniques. Given rapid technological advances, the question for companies now is how to integrate new data science capabilities into their operations and strategies—and position themselves in a world where analytics can upend entire industries. Leading companies are using their data science capabilities not only to improve their core operations but also to launch entirely new business models.
Big Data Analytics | What Is Big Data Analytics? | Big Data Analytics For Beg...Simplilearn
The presentation about Big Data Analytics will help you know why Big Data analytics is required, what is Big Data analytics, the lifecycle of Big Data analytics, types of Big Data analytics, tools used in Big Data analytics and few Big Data application domains. Also, we'll see a use case on how Spotify uses Big Data analytics. Big Data analytics is a process to extract meaningful insights from Big Data such as hidden patterns, unknown correlations, market trends, and customer preferences. One of the essential benefits of Big Data analytics is used for product development and innovations. Now, let us get started and understand Big Data Analytics in detail.
Below are explained in this Big Data analytics tutorial:
1. Why Big Data analytics?
2. What is Big Data analytics?
3. Lifecycle of Big Data analytics
4. Types of Big Data analytics
5. Tools used in Big Data analytics
6. Big Data application domains
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
The New Enterprise is adopting
new tools and technology that
utilize data, mobilize their
workforce, and increase
collaboration throughout the
organization. In this new report, SVB Analytics examines the underlying industry sectors supporting this new business environment and offers data on venture funding, revenue models and valuations.
The Identification of the ROI of Big Data is Pending on the Democratization of the Business Insights Coming from Advanced and Predictive Analytics of that Information
How to identify the Return on Investment of Big Data / CIO (Infographic)suparupaa
The Identification of the ROI of Big Data is Pending on the Democratization of the Business Insights Coming from Advanced and Predictive Analytics of that Information
Tracxn Research - Finance and Accounting Landscape, August 2016Tracxn
$3.3B has been invested in the finance and accounting startup landscape in 2015/2016, which witnessed the highest funding activity in 2015 ($2.6B, 124 rounds).
A look at the evolution of analytics and its revolutionary potential to transform ordinary businesses, power new business models, enable innovation, and deliver greater value. http://www2.deloitte.com/us/en/pages/deloitte-analytics/articles/analytics-trends.html
Similar to Tracxn Big Data Analytics Landscape Report, June 2016 (20)
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Tracxn - Top Business Models in High Tech - 27 Oct 2023Tracxn
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...2023240532
Quantitative data Analysis
Overview
Reliability Analysis (Cronbach Alpha)
Common Method Bias (Harman Single Factor Test)
Frequency Analysis (Demographic)
Descriptive Analysis
2. Big Data Analytics, June 2016
Tracxn
World’s Largest Startup Research Platform
2
To receive the full 118 page report, write to us at bd@tracxn.com
3. Big Data Analytics, June 2016
Contents
Topic Page No.
Scope of Report 05
Entrepreneur Activity 07
Investment Trend 09
Who is Investing 17
Exit Outlook - IPO, Acquisitions 21
Big Data Analytics – Insights, Market Trends 23
Sub Sector Analysis 25
Company List 43
Team 118
3
3
4. Big Data Analytics, June 20164
Illustrative Sectors We Track
ENTERPRISE
INFRASTRUCTURE
TECH
SECURITY
STORAGE
NETWORKING
MOBILITY
IT OPS
CLOUD INFRASTRUCTURE
API MANAGEMENT
BIGDATA INFRASTRUCTURE
INTERNET OF THINGS
3D PRINTING
EDUCATION
CONSUMER
MARKETPLACES
SUBSCRIPTION COMM.
FOOD TECH
INTERNET FIRST BRANDS
UBER FOR X
SECOND HAND GOODS
TRAVEL
GAMING
EDUCATION IT
SELF LEARNING
HEALTHCARE
MOBILE
MOBILE COMMERCE
MOBILE PAYMENTS
MOBILE MARKETING
MOBILE DEV TOOLS
MOBILE HEALTH
MOBILE GAMING
MOBILE LEARNING
MOBILE COMMUNICATION
LIFE SCIENCES
DIGITAL HEALTH
FINTECH
ENTERPRISE
APPLICATIONS
SAAS
MOBILE-FIRST ENT. APPS
INTELLIGENT ENT. APPS
OPEN SOURCE
RETAIL TECH
MARKETING TECH
BIG DATA ANALYTICS
VERTICAL SAAS
BITCOIN
PAYMENTS
5. Big Data Analytics, June 20165
Sector Overview
Scope of report
The report covers companies that provide Big Data Analytics solutions for data discovery, data integration, visualization, data
science and advanced predictive analytics. It excludes services and consultancies that use tech product of other companies for
data analytics.
Report also covers companies that provide Big Data Analytics platform for Heavy Industries, Finance and other verticals.
The funding details provided in the report include venture capital/private equity funding rounds and excludes debt financing and
grants/prize money.
6. Big Data Analytics, June 2016
Scope of Report
Entrepreneur Activity
Investment Trend
Who is Investing
Exit Outlook - IPO, Acquisitions
Big Data Analytics – Insights, Market Trends
Sub Sector Analysis
Company List
Team
6
6
7. Big Data Analytics, June 20167
YoY – Number of companies founded
10
24
38
37 37
27
0
8
16
24
32
40
2010 2011 2012 2013 2014 2015
No.ofCompanies
Alteryx Looker ThoughtSpot BBD Uptake Ndustrial.io
DataSift Platfora Trifacta Dato UNIFi Software Outlier
8. Big Data Analytics, June 2016
Scope of Report
Entrepreneur Activity
Investment Trend
Who is Investing
Exit Outlook - IPO, Acquisitions
Big Data Analytics – Insights, Market Trends
Sub Sector Analysis
Company List
Team
8
8
9. Big Data Analytics, June 20169
YoY – Number of Rounds and Total Funding
$128M
$88M
$227M
$346M $353M
$847M
$1B
$1.8B
$399M14
18
19
26
45
68
51
73
25
0
16
32
48
64
80
0
400
800
1200
1600
2000
2008 2009 2010 2011 2012 2013 2014 2015 2016
NumberofRounds
FundingAmount(inMillions)
Funding Amount Number of Rounds
16. Big Data Analytics, June 2016
Scope of Report
Entrepreneur Activity
Investment Trend
Who is Investing
Exit Outlook - IPO, Acquisitions
Big Data Analytics – Insights, Market Trends
Sub Sector Analysis
Company List
Team
6
16
17. Big Data Analytics, June 201617
Most Active Investors in Sector
17
15
14
13
10
9 9
8 8 8
0
4
7
11
14
18
NEA Andreessen
Horowitz
Accel Intel Khosla Madrona Redpoint A Ventures GE Ventures Kleiner Perkins
TotalNumberofCompanies
Pentaho SnapLogic Trifacta Guavus Ayasdi Context Relevant Looker DataSift Ayasdi OSIsoft
DataRobot Platfora Zoomdata Endeca ThoughtSpot Dato Datameer DataRobot Maana Inc Ayasdi
20. Big Data Analytics, June 2016
Scope of Report
Entrepreneur Activity
Investment Trend
Who is Investing
Exit Outlook - IPO, Acquisitions
Big Data Analytics – Insights, Market Trends
Sub Sector Analysis
Company List
Team
0
20
21. Big Data Analytics, June 201621
Major Acquisitions in last one year
Date Company Acquirer Deal size Overview
Total
Funding
04/20/2016 lexmark.com
Lexmark
(Lexington, 1990)
apexmic.com 4.0B
Enterprise Search
03/22/2016 sense.io
Sense
(California, 2012)
cloudera.com
Data Science Platform as a Service
Granite Ventures LLC, Illuminate
$1.1M
01/19/2016 aimlogic.com
AimLogic
(Las Vegas, 2014)
nccdirect.com
Predictive Analytics for lead scoring
01/16/2016 iris-
analytics.com
Iris Analytics
(Frankfurt, 2000)
ibm.com
Real-time decisions for improved fraud and risk control
01/14/2016 listenlogic.com
ListenLogic
(San Jose, 2007)
marlinequity.com
Social Business Intelligence Analytics
11/18/2015 syncsort.com
Syncsort
(Woodcliff Lake, 1968)
clearlakecapital.com
Big Data Integration
10/26/2015 parstream.com
ParStream
(Cologne, 2008)
cisco.com
Analytics for IoT
CrunchFund, Khosla Ventures, Baker Capital, Tola Capital, Data
Collective
$13.6M
08/7/2015 informatica.com
Informatica
(Redwood City, 1993)
permira.com Data Integration Software
22. Big Data Analytics, June 2016
Scope of Report
Entrepreneur Activity
Investment Trend
Who is Investing
Exit Outlook - IPO, Acquisitions
Big Data Analytics – Insights, Market Trends
Sub Sector Analysis
Company List
Team
2
22
23. Big Data Analytics, June 201623
Big Data Analytics – Insights, Market Trends
• Big Data market was estimated to be $6.8 billion in 2012; and is projected to grow by almost 40% every year. [Source 1]
• The global Business Intelligence and Analytics Software Market is expected to grow from $17.90B in 2014 to $26.78B by
2019, at a Compound Annual Growth Rate (CAGR) of 8.4%. [Source 2]
• Big Data Analytics saw significant amount of funding in 2015/16 with total funding of $2.26B.
• Contextual Data Analytics saw significant increase in funding from 2014 to 2015, receiving ~1B in 2015. Palantir received the
most amount.
• Advanced analytics experienced a rise in demand as analytics companies started deploying predictive models in IoT, Finance,
and other real-world use cases. Adaptive Predictive Technologies got acquired by MasterCard for $600M.
• Data Science Platform is gaining popularity as increasing demand for data models needed for Predictive Analytics.
• Self Service Data Discovery platforms helps business users to get insights from raw data by providing advanced visualization
techniques such as easy querying language, natural language search or visual analytics, thus reducing the dependency on IT
and analysts.
• Self-service Data Discovery platforms using Hadoop and Apache Spark is expected to grow.
-Source 1 -Source 2
24. Big Data Analytics, June 2016
Scope of Report
Entrepreneur Activity
Investment Trend
Who is Investing
Exit Outlook - IPO, Acquisitions
Big Data Analytics – Insights, Market Trends
Sub Sector Analysis
Company List
Team
4
24
25. Big Data Analytics, June 201625
June 2016Tracxn BlueBox : Big Data Analytics
280+ companies in the sector, $5 B invested in last 5 years, $2.26 B invested in 2015/16
26. Big Data Analytics, June 201626
Top Business Models by Funding
$2.7B
$860M
$767M
$540M
$354M
$200M $187M $173M $103M
$13M
0
500
1000
1500
2000
2500
3000
Contextual Data
Analytics
Data Analytics Data Preparation Verticals Data Discovery Streaming Data
Analytics
Data
Visualization
Search Based
Analytics
Data Science
Platform
Big Data Analytic
Suites
TotalFundingAmount(inMillions)
# Cos. 17 77 35 80 17 22 6 5 16 7
Avg. Age 2009.8 2008.3 2005.7 2008.4 2009.7 2008.7 2008.8 2006.2 2010.2 2003.6
Palantir Alteryx Attivio OSIsoft Platfora Qubole Birst Inc. ThoughtSpot Revolution Analytics QlikTech
Guavus Predictive Technologies Talend Uptake Datameer StreamBase CartoDB Endeca Continuum Ingensi
27. Big Data Analytics, June 201627
Contextual Data Analytics – Business Model
Description
28. Big Data Analytics, June 201628
Contextual Data Analytics – Entrepreneur Activity
and Investment Trend
29. Big Data Analytics, June 201629
Contextual Data Analytics – Most Funded
Companies
42. Big Data Analytics, June 2016
Scope of Report
Entrepreneur Activity
Investment Trend
Who is Investing
Exit Outlook - IPO, Acquisitions
Big Data Analytics – Insights, Market Trends
Sub Sector Analysis
Company List
Team
2
42
43. Big Data Analytics, June 201643
Big Data Analytics – Company List
DETAILS CLOSE TO 288 COMPANIES
(169 FUNDED AND 119 UNFUNDED COMPANIES)
COVERS THE FOLLOWING SECTORS
Contextual
Data
Analytics
Data
Analytics
Data
discovery
Data
Preparation
Data
Science
Platform
Data
Visualization
Search
Based
Analytics
Streaming
Data
Analytics
Verticals Services
Big Data
Analytics
Suite
44. Big Data Analytics, June 201644
Contextual Data Analytics (1/5)
Company Details Funding Investors
Palantir [Palo Alto, 2004]: Palantir's platforms provide data analysis capabilities to enterprises through its products
Gotham and Metropolis. Gotham integrates structured and unstructured data and enables discovery, analysis, and
knowledge management. Metropolis conducts quantitative data analysis, data integration, and information
management. Palantir's products are extensively used by federal agencies of the U.S. intelligence, state governments,
local governments, and financial institutions around the world. Some of the solutions include case management, anti-
fraud, disaster preparedness, law enforcement, defense, and insurance analytics. Acquisitions: Kimono labs in
February 2016; FT Technologies in February 2015; Propeller in July 2014; Poptip in July 2014; Voicegem in February
2013
$2.32B
Ulu Ventures, Founders Fund, Morgan
Stanley, Glynn Capital Management,
PENSCO, ARTIS Ventures, YVentures,
sfsentry.com, Reed elsevier ventures,
In-Q-Tel
Guavus [San Mateo, 2006]: Guavus provides Big Data analytics solutions, which enable intelligent decision-making for
network operations, marketing, customer care and monetization. The company’s data analysis offering is specifically
used by telecommunications providers to give these companies insights on network performance, device and
application usage, content and subscriber behavior to optimize network capacity and increase revenues. The company
counts 4 of the top 5 mobile network operators, 3 of the top 5 Internet Backbone providers, as well as 80% of cable
MSOs in North America as customers. It currently Claims to analyze more than 50% of all US mobile data traffic and
processes more than 2.5 petabytes of data per day. Deployments span retail, enterprise and wholesale channels
across data, wireless, wire-line and multimedia product offerings.
$137M
Artiman, Goldman Sachs, QuestM,
Singtel Innov8, Translink Capital,
Investor, Intel Capital, Investor
Growth Capital, Sofinnova Ventures,
Artiman
Ayasdi [Palo Alto, 2008]: Ayasdi automates and accelerates insight discovery. The company’s Machine Intelligence
software employs Topological Data Analysis (TDA), to simplify the extraction of knowledge from the most complex
data sets confronting organizations today. Developed by Stanford computational mathematicians, Ayasdi’s approach
combines machine-learning algorithms, abundant compute power and topological summaries to revolutionize the
process for converting data into business impact.
$108.13M
ventures.citi.com, Institutional
Venture Partners, Kleiner Perkins,
Khosla Ventures, Centerview Capital,
Draper Nexus, Floodgate, GE Ventures
Context Relevant [Seattle, 2012]: Context Relevant is a leader in Big Data analytics. Context Relevant has developed
an analytics system that ingests data, determines what’s important, and creates a problem-specific solution that can
be deployed while continually learning.The proprietary high-performance machine learning technology accelerates
analytics and actionable insight. It is backed by some of the major companies in the Financial Services Domain.
$44.3M
Vulcan Capital, work bench, new york
life insurance company, Bloomberg
Beta, Goldman Sachs, Bank of
America, Formation, MADRONA,
rolling bay ventures
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
45. Big Data Analytics, June 201645
Contextual Data Analytics (2/5)
Company Details Funding Investors
Interana [Menlo Park, 2012]: Interana is a fast and scalable event-based analytics solution that answers critical
business questions on how customers behave and products are used. With Interana, key business metrics that matter
most in a data-driven world - such as growth, retention, conversion and engagement. Interana allows customers to
discover and investigate these key insights easily through its visual and interactive interface. Streaming data and data
at rest are analyzed together, enabling companies to see how real-time snapshots fit into historical trends. It analyze
massive volumes of call detail records for understanding how users behave and interact with products and services.
Sony, Tinder, Jive, Bloomboard and Orange are among its customers.
$28.2M
Y Combinator, SV Angel, Fuel Capital,
Data Collective, Battery, Index
Ventures, AME Cloud Ventures
Infobright [Toronto, 2005]: Infobright develops analytic database designed for applications and data marts that
analyze large volumes of machine generated data such as web data, network logs, telecom records, stock tick data
and sensor data. Solution is capable of storing and analyzing sensor data at IoT scale. Common use cases are for
enterprises, SaaS and software companies in online businesses, telecommunications, financial services and other
industries to provide rapid analysis of critical business data.
$21M Sun Microsystems, Flybridge, RBC
Spire [Bangalore, 2008]: Spire offers big data based enterprise technology that offers various solutions for supply
chain management, customer relationship management, fraud intelligence, talent growth management and predictive
talent intelligence. Its technology solutions enable enterprises to make informed decisions with accurate demand-
supply mapping from any combination of structured and unstructured data. Also provides fraud detection solutions by
pulling in data from unstructured data such as documents, emails, SMS and reviews. The company has previously
raised $1 million in a seed round from several angel investors.
$8M
Market6 [Ohio City, 2006]: Market6 is a big data analytics company that leverages retailers operational data to
improve overall business performance and enable better collaboration with suppliers. Our flagship is DemandView®,
a suite of tools, reporting, and predictive analytics provided via Information Services or SaaS solutions that provides a
real-time, forward-looking view of sales, promotion and distribution performance. DemandView is used by the largest
supermarket chain in the US, and is accessed by over 400 supplier partners
$5.5M Sevin Rosen Funds
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
46. Big Data Analytics, June 201646
Contextual Data Analytics (3/5)
Company Details Funding Investors
dMetrics [Brooklyn, 2009]: dMetrics is building the definitive map of consumer decision-making. It operated on a
NLP based engine and has the team of MIT PhDs which have built a platform to analyze thousands of social networks,
blogs, and forums, identifying and connecting people, their decisions about products, and rationale for these
decisions. The result is a dynamic interest graph, helping companies and individuals make better decisions about
products to use, campaigns to run, and companies to invest in. Its clients (from Fortune 500 to non-profits) use
dMetrics to get the most accurate, unbiased, and transparent view of people’s actions, tracing decision making all the
way from high-level market insights to high-value discussions. Understanding what people do - and why - is the next
frontier of text analytics. Clicks, Likes and Retweets do not representatively convey the voice of the consumer,
comprising a tiny portion of the information contributed by Internet users. Most of the Internet (other than photos of
kittens) is conversational: blog posts, forum discussions, Twitter dialogues. It claims to have a platform that extracts
consumer decisions from billions of online conversations. So far, its platform has served clients in healthcare which
has resulted in the database of healthcare-centric insights about 14,000+ products. Similar repositories of consumer
insights for CPG, telecom, and banking industries are underway.
$2.3M National Science Fdn
deepsense.io [Menlo Park, 2014]: DeepSense product SeaHorse enables users to build Spark applications using an
intuitive visual environment without the need to write any code. By dragging and dropping blocks from the palette of
available operations users are able to design any data workflow that contains such steps as: ETL, data manipulation,
clean-up and reports, even up to advanced predictive modeling. It has a open-source community edition while the
enterprise edition offers some more features.
$2M CodiLime
Aureus Analytics [Mumbai, 2013]: Provider of predictive analytics and big data ready platforms for insurance
companies and banks. Their platform, ASAP, allows users to create, publish and execute analytical models. Focused on
Europe &; the South East Asian Market. Customers include Bharti AXA Life Insurance, Aegon Religare Life Insurance
and General Insurance Council of India among others. Headquartered in Singapore with R&;D in Mumbai. Secured
angel funding of $850k from a group of individual investors through LetsVenture.
$850k
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
47. Big Data Analytics, June 201647
Contextual Data Analytics (4/5)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
48. Big Data Analytics, June 201648
Contextual Data Analytics (5/5)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
49. Big Data Analytics, June 201649
Data Analytics (1/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
50. Big Data Analytics, June 201650
Data Analytics (2/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
51. Big Data Analytics, June 201651
Data Analytics (3/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
52. Big Data Analytics, June 201652
Data Analytics (4/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
53. Big Data Analytics, June 201653
Data Analytics (5/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
54. Big Data Analytics, June 201654
Data Analytics (6/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
55. Big Data Analytics, June 201655
Data Analytics (7/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
56. Big Data Analytics, June 201656
Data Analytics (8/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
57. Big Data Analytics, June 201657
Data Analytics (9/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
58. Big Data Analytics, June 201658
Data Analytics (10/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
59. Big Data Analytics, June 201659
Data Analytics (11/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
60. Big Data Analytics, June 201660
Data Analytics (12/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
61. Big Data Analytics, June 201661
Data Analytics (13/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
62. Big Data Analytics, June 201662
Data Analytics (14/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
63. Big Data Analytics, June 201663
Data Analytics (15/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
64. Big Data Analytics, June 201664
Data Analytics (16/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
65. Big Data Analytics, June 201665
Data Analytics (17/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
66. Big Data Analytics, June 201666
Data Analytics (18/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
67. Big Data Analytics, June 201667
Data Analytics (19/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
68. Big Data Analytics, June 201668
Data Discovery (1/4)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
69. Big Data Analytics, June 201669
Data Discovery (2/4)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
70. Big Data Analytics, June 201670
Data Discovery (3/4)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
71. Big Data Analytics, June 201671
Data Discovery (4/4)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
72. Big Data Analytics, June 201672
Data Preparation (1/9)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
73. Big Data Analytics, June 201673
Data Preparation (2/9)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
74. Big Data Analytics, June 201674
Data Preparation (3/9)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
75. Big Data Analytics, June 201675
Data Preparation (4/9)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
76. Big Data Analytics, June 201676
Data Preparation (5/9)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
77. Big Data Analytics, June 201677
Data Preparation (6/9)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
78. Big Data Analytics, June 201678
Data Preparation (7/9)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
79. Big Data Analytics, June 201679
Data Preparation (8/9)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
80. Big Data Analytics, June 201680
Data Preparation (9/9)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
81. Big Data Analytics, June 201681
Data Science Platform (1/5)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
82. Big Data Analytics, June 201682
Data Science Platform (2/5)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
83. Big Data Analytics, June 201683
Data Science Platform (3/5)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
84. Big Data Analytics, June 201684
Data Science Platform (4/5)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
85. Big Data Analytics, June 201685
Data Science Platform (5/5)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
86. Big Data Analytics, June 201686
Data Visualization (1/2)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
87. Big Data Analytics, June 201687
Data Visualization (2/2)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
88. Big Data Analytics, June 201688
Search Based Analytics
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
89. Big Data Analytics, June 201689
Streaming Data Analytics (1/6)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
90. Big Data Analytics, June 201690
Streaming Data Analytics (2/6)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
91. Big Data Analytics, June 201691
Streaming Data Analytics (3/6)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
92. Big Data Analytics, June 201692
Streaming Data Analytics (4/6)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
93. Big Data Analytics, June 201693
Streaming Data Analytics (5/6)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
94. Big Data Analytics, June 201694
Streaming Data Analytics (6/6)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
95. Big Data Analytics, June 201695
Verticals->Finance (1/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
96. Big Data Analytics, June 201696
Verticals->Finance (2/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
97. Big Data Analytics, June 201697
Verticals->Finance (3/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
98. Big Data Analytics, June 201698
Verticals->Finance (4/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
99. Big Data Analytics, June 201699
Verticals->Finance (5/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
100. Big Data Analytics, June 2016100
Verticals->Finance (6/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
101. Big Data Analytics, June 2016101
Verticals->Finance (7/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
102. Big Data Analytics, June 2016102
Verticals->Finance (8/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
103. Big Data Analytics, June 2016103
Verticals->Finance (9/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
104. Big Data Analytics, June 2016104
Verticals->Finance (10/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
105. Big Data Analytics, June 2016105
Verticals->Finance (11/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
106. Big Data Analytics, June 2016106
Verticals->Finance (12/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
107. Big Data Analytics, June 2016107
Verticals->Finance (13/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
108. Big Data Analytics, June 2016108
Verticals->Finance (14/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
109. Big Data Analytics, June 2016109
Verticals->Finance (15/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
110. Big Data Analytics, June 2016110
Verticals->Finance (16/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
111. Big Data Analytics, June 2016111
Verticals->Finance (17/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
112. Big Data Analytics, June 2016112
Verticals->Finance (18/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
113. Big Data Analytics, June 2016113
Verticals->Finance (19/19)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
114. Big Data Analytics, June 2016114
Services
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
115. Big Data Analytics, June 2016115
Big Data Analytic Suites (1/2)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
116. Big Data Analytics, June 2016116
Big Data Analytic Suites (2/2)
Contextual Data
Analytics
Data
Analytics
Data
discovery
Data Preparation
Data Science
Platform
Data
Visualization
Search Based
Analytics
Streaming Data
Analytics
Verticals Services
Big Data
Analytics Suite
117. Big Data Analytics, June 2016
Scope of Report
Entrepreneur Activity
Investment Trend
Who is Investing
Exit Outlook - IPO, Acquisitions
Big Data Analytics – Insights, Market Trends
Sub Sector Analysis
Company List
Team
7
117
118. Big Data Analytics, June 2016118
Team
Manish Jaiswal
Senior Analyst, Big Data Analytics
Harini Kancharana
Lead Analyst, Enterprise Infrastructure