3. 2013: The Year of Big Data
• 2013: Year of larger scale adoption of big
data.
• 42% state they have invested in big data, or
are planning to do so within a year.
• By 2015, 20% of Global 1000 organizations
will have established a strategic focus on
"information infrastructure”.
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4. Top Trends: Big Data Everywhere?
# Trend Quote
1 Big Data The most important aspects of big data are the benefits that can be realized
by an organization.
4 The Logical Data These new warehouses force a complete rethink of how data is manipulated,
and where in the architecture each type of processing occurs that supports
Warehouse transformation and integration.
5 NoSQL DBMSs NoSQL DBMSs — key-value stores, document-style stores, and table-style
and graph databases — are designed to support new transaction,
interaction and observation use cases involving Web scale, mobile, cloud and
clustered environments.
6 In-Memory Opens unprecedented and partially unexplored opportunities for business
innovation (for example, via real-time analysis of big data in motion) and
Computing cost reduction (for example, through database or mainframe off-loading).
7 Chief Data Officer Goal: to structure and manage information throughout its life cycle, and to
better exploit it for risk reduction, efficiency and competitive advantage.
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6. ORIGIN OF THE TERM: 2001
In a 2001 research report, META Group (now Gartner) analyst Doug Laney defined
data growth challenges and opportunities as being three-dimensional, i.e. increasing
volume (amount of data), velocity (speed of data in and out), and variety (range of
data types and sources).
TBDI Definition of Big data: Big Data is a term applied to voluminous data objects that
are variety in nature – structured, unstructured or a semi-structured, including sources
internal or external to an organization, and generated at a high degree of velocity with
an uncertainty pattern, that does not fit neatly into traditional, structured, relational
data stores and requires strong sophisticated information ecosystem with high
performance computing platform and analytical capabilities to
capture, process, transform, discover and derive business insights and value within a
reasonable elapsed time.
Source: http://en.wikipedia.org/wiki/Big_data
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7. GARTNER
• Volume: The increase in data volumes within enterprise systems is caused by
transaction volumes and other traditional data types, as well as by new types of
data. Too much volume is a storage issue, but too much data is also a massive
analysis issue.
• Variety: IT leaders have always had an issue translating large volumes of
transactional information into decisions — now there are more types of
information to analyze — mainly coming from social media and mobile (context-
aware). Variety includes tabular data (databases), hierarchical
data, documents, e-mail, metering data, video, still images, audio, stock ticker
data, financial transactions and more.
• Velocity: This involves streams of data, structured record creation, and
availability for access and delivery. Velocity means both how fast data is being
produced and how fast the data must be processed to meet demand.
Source: http://www.gartner.com/it/page.jsp?id=1731916
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8. IDC
• Deployments where the data collected is over 100 terabytes (TB). IDC is
using data collected, not stored, to account for the use of in-memory
technology where data may not be stored on a disk.
• Deployments of ultra-high-speed messaging technology for real-time,
streaming data capture and monitoring. This scenario
represents Big Data in motion as opposed to Big Data at rest.
• Deployments where the data sets may not be very large today, but are
growing very rapidly at a rate of 60% or more annually.
Source: http://www.idc.com/getdoc.jsp?containerId=prUS23355112#.UWpUJJPkvzw
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10. Gartner BI Summit Stats (2013)
• Few companies use predictive (13%) or
prescriptive (3%) Analytics.
• 75% of current data warehouses will not
scale to meet the new velocity and
complexity of data demands
• 86% of companies cannot deliver the
right information at the right time
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11. IT Struggles with Big Data
• 79% of businesses with 501 to 1000 employees
say their IT departments view big data as a
"significant challenge," versus just 55% of
organizations with more than 3,000 workers.
• One-third of IT managers, faced with have to
attend to daily short-term challenges, struggle
with long-term strategic planning related to big
data and other forward-looking technical matters.
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12. McKinsey on Big Data
• 200 terabytes of stored data per company
with more than 1,000 employees.
• A retailer using big data to the full has the
potential to increase its operating margin by
more than 60 percent.
• Services enabled by personal-location data
can allow consumers to capture $600 billion
in economic surplus.
Source http://bit.ly/15cB6Sj
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13. Big Data Need Better Software
By 2015, Big Data demand will reach 4.4
million jobs globally, but only one-third of
those jobs will be filled.
72% of respondents plan to increase their
spending in analytics this year (…). However,
60% actually said they don't have the skills
required to effectively use analytics.
Gartner, 2012-2013
53% of big data-focused companies say
analytics experts will be tough to find for the
next two years.
InformationWeek, 2012
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15. [MISSION]
BIG DATA ANALYTICS FOR EVERYONE
SiSense Prism™: 3-components-in-one
Analytical Database and Automatic ETL
1
Ad-hoc Reporting and Discovery
2
Analytics & Web Dashboards
3
[www.sisense.com]
16. [CUSTOMERS]
GLOBAL BRANDS AND START-UPS
Customers in 49 countries
[www.sisense.com]
17. [TESTIMONIALS]
We can finally query huge amount of data without
breaking a sweat!
It's fantastic how easy it is for non-technical people
to use, and how fast the system responds
The volume of data we deal with choked the
competitor’s tool
“Prism has greatly minimized the workload for our investigation teams
by quickly combining multiple theft-related data sources"
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18. [REVIEWS]
“SiSense makes analytics dead simple”
“The company seems to have a knack for winning
people over with its technology”
“I sense the big boys will be in for a nasty shock”
“If you’ve been wrestling with the size limitations of other
tools, do yourself a favor & try SiSense. There’s nothing else on
the market that crunches big data so easily and inexpensively.”
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19. [ANALYTICAL DATABASE] 1
SISENSE ELASTICUBE™: Simplicity and Scalability
Columnar DataStore
• Optimized for Speed & Storage
• Compression
• Automatic ETL
In-Memory Query Engine
• Engineered for Infinite Memory
• Query Recycler for Multi-User
• Parallel Processing
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20. [AD-HOC DISCOVERY] 2
SISENSE BI STUDIO™: Usability and Speed
Business Discovery
• Excel-like Ad-Hoc Data Analysis.
• Drag-and-Drop, Template Library
for filters, hierarchies & measures.
Simple to Sophisticated
• Graphical Editor allows any user to
build their own calculations.
• No Proprietary Scripting: Optimized
for standard SQL language.
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21. [ANALYTICS ON THE WEB] 3
SISENSE WEB™: Open and Collaborative
Built for the Web
• Stunning Visualizations & Interactive
Dashboards with Zero-Footprint.
• Dynamic Drilling, Filtering & Sorting
in ANY Browser.
• Deployed as HTML 5/Javascript.
Collaborative and Mobile
• Share Securely via the Web.
• Export to Excel, PowerPoint, PDF.
• View & Interact via Compatible
Mobile Browsers.
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2,053 CIOs, representing more than $230 billion in CIO IT budgets and covering 36 industries in 41 countries.
2,053 CIOs, representing more than $230 billion in CIO IT budgets and covering 36 industries in 41 countries.
2,053 CIOs, representing more than $230 billion in CIO IT budgets and covering 36 industries in 41 countries.
Other customer statsTarget1,755 stores/49 states/350,000 team members WWWix"29M Wix users. 1M new every month11 ElastiCubes of 30GB each - that's 3TB of data3,000 campaigns/monthAll this with a team of less than 5 people (from hadoop to visualization).“Wefi13 tables in one model, with average table size of more than 5 million rows. Average table size now exceeds 500 million rows.$80M in Sales (80 people). Company had already used a leading in-memory technology – but the software’s performance was sub-par. Plastic Jungle"18mo of history in less than 1 minute.Saved $100k by choosing SiSense.“Galaxy2,500 customers worldwide. 4 to 5 billions of records of data in minutes. From 10-12 minutes to 15 seconds – that’s close to a 50X performance boost