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UNITING INTERNET OF THINGS
AND BIG DATA
YOU CAN’T DO THE “THINGS” OF IoT IN A TRADITIONAL DATA WAREHOUSE ENVIRONMENT
IoT is defined by many to be the “collection, processing, and analysis of information from sensors on a large number of disparate devices.”
The Internet of Things aligns well with big data initiatives because they share the same core attributes: Data collection from multistructured data sources Data management at a large scale Complex processing
NEARLY 50% OF RESPONDENTS STATED INTERNET OF THINGS IS
ESSENTIAL OR IMPORTANT TO THEIR ORGANIZATIONAL STRATEGIES
Adopted and an essential part of our business
Adopted and an important part of our business
Adopted and mostly supplemental to other
types of computing
Planned for adoption in the near future (3-6 months)
Being reasearched in the next year (6-12 months)
Not planned for research or adoption
Percentage of Respondents
THESE PROJECTS HAVE A LOW-LATENCY REQUIREMENT
IN PROCESSING
TO MEET THOSE IoT OBJECTIVES...
Real-time/near real-time
processing of data
Intra-hour processing of
data
Intra-day processing
of data
Next day processing
Processing is relatively
time-insensitive
Workload LatencyIntra-day
Near real-time
Time insensitive
32.4% 23.3%
19.8%
13.9%10.5%
Real-time streaming data integration
Change data capture (CDC) (e.g., tracking and executing on changes made to enterprise)
Multipoint data services layer (e.g., data visualization, data federation)
Extract-load-transform processing in data store/database (ELT)
Extract-transform-load processing external to data store/database (ETL)
Data replication (e.g., standardized duplication of enterprise data sources)
Batch, bulk data integration
Native operating system or database utilities
Point-to-point integration bus
...STANDARD ETL WON’T WORK FOR THE WORLD OF IoT. WE NEED TO MOVE BEYOND BATCH TO
MORE STREAMING TECHNOLOGIES BASED ON OPERATIONAL PROCESSES AND THE
APPLICATIONS THAT DRIVE THOSE “THINGS”
12.1%
11.5%
11.2%
10.8%
10.0%
12.0%
11.2%
10.8%
10.0%
MOST POPULAR BIG DATA PROJECT STRATEGY IS TO USE CONFIGURABLE APPLICATIONS TO
IMPLEMENT BIG DATA PROJECTS
Customizable applications from external provider
Hand-coded development by internal resource(s)
Custom development by
external consultant(s)
Productized development by external provider
Stand-alone products from external provider(s)
Bespoke development by internal
staff contractor(s)
20.7%
17.7%16.3%
15.7%
15.0%14.3%
Project ImplementationStrategy
Configurable Products
Manual Development
SNAPLOGIC EMPOWERS ORGANIZATIONS TO INTEGRATE BIG DATA AND STREAMING
INTERNET OF THINGS APPLICATIONS
HIGHLY CONFIGURABLE WITHOUT TECHNICAL
RESOURCES
HANDLES STREAMING AND BATCH DATA
INTEGRATE DATA FROM MULTIPLE SOURCES,
INCLUDING MQTT AND OTHER IOT PROTOCOLS
UnifiedPlatform
Connects data,applications, APIs,and IoT devices
faster
Self-servicefor “citizenintegrators”
and developers
In 2014, EMA and 9sight Consulting surveyed 351 diverse business and technology professionals to provide their insights on big datastrategies and implementation practices, including Internet of Things strategies and implementations. The 2014 survey instrument wasexecuted in December 2014.
Hybrid platformbuilt for
elastic scale
300+ intelligentapplication anddata connectors
Drag-and-dropSnapReducepipelines andHadooplex big
data processing
ProductiveUX
ModernArchitecture
ComprehensiveConnectivity
Hadoopfor Humans
SNAPLOGIC PROVIDES . . .
17.1%
29.3%
16.8%
10.5%
10.5%
15.7%
TO LEARN MORE, VISIT
www.SnapLogic.com