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ADAPTIVE INTELLIGENCE
ON MODERN DATA
Data Stack is Changing to Enable Data-
Driven Enterprises
Descriptive	
Analytics
Diagnostic	
Analytics
What	happened?
Will	it	happen	again?
What	should	I	
do	now?
Mostly	Structured	Data
Predictive	
Analytics
Prescriptive	
Analytics
Why	did	it	happen?
Blend	of	Structured,	Unstructured,	and	
Multi-structured	Data
Advanced	Analytics
Basic	Analytics
But…Traditional BI Tools are Stuck in the Past
Only	Understands Structured	Data
*
Understands	Structured,	Unstructured,	and	
Multi-structured	Data	+	Machine	Learning
Understands	Some	Unstructured,	and	Multi-
structured	Data
The Hidden Costs Of Not Understanding
Modern Data
Pre-define	schemas
Extract	data	using	underlying	
query	language
Write	custom	code	or	use	ODBC	drivers	
or	ETL	to	move	data	to	relational	tables
1 2 3
• Newer NoSQL data must be shoehorned back into relational structures
• Forces duplication of data increasing cost of information and risk
• Potential performance impacts when processing large datasets
• IT teams must be involved to move and manipulate NoSQL data
Adds	months	
to	projects
Adds	
platform	
complexity
Requires	
specialized	
resources
Limits	data	
discovery
Changes	are	
expensive
Increased
TCO
Advanced Analytics on Modern Data
Integrate	Machine	
Learning
Data-Driven	
Triggers
Unified	View	of	
Enterprise	Data
Natively	Understands	Structured,	
Unstructured,	and	Multi-structured	
Modern	Data
Descriptive	
Analytics
Diagnostic	
Analytics
Predictive	
Analytics
Prescriptive	
Analytics
Native	NoSQL	
Analytics
Knowi Adaptive Intelligence Platform
Knowi Advanced Analytics
Native NoSQL Integration
•No ETL. No ODBC drivers.
•Schema on read for instant data
discovery
Unified View of Data
•Multi-datasource joins
•Multi-structured nested datasets
•SQL, NoSQL, RDBMS, API,
CSV/JSON
Native Query Generation
•Drag & drop query generator
•Integrated post processing
•No specialize knowledge
Integrated AI
•Use built-in or bring your own
Machine Learning algorithms
•Data-driven triggers
All Users Welcome Here
•Technical and business users
•Share, collaborate, and embed
insights, print to PDF
Enterprise Scale
•Configure query execution to
optimize for business use case
•Cloud, OnPrem or Hybrid
Deployment options
Multiple Deployment Options
• Queries are pushed down
• Datasets are stored in
Knowi Cloud
Agent
HybridCloud On Prem
• Queries are pushed down to database
• Data stays on premise
• Agent accesses datasets for report generation
• Everything is done on
premise
• Customer maintains
server environment
About Knowi
10
FOUNDED
in	2014 with	
headquarters	in	
Oakland
TRUSTED
By	a	diverse	global	
customer	base
VISION
brings	AI	to	BI	for	
modern	data	
analytics
What Our Customers Are Saying
Knowi	helped	Lemonaid in	a	number	of	ways	to	be	able	to	quickly	access	critical	
business	 information	from	our	secure	HIPAA	compliant	data.	Whether	it’s	for	
internal	purposes	or	the	partners,	having	very	easy	to	use	and	quick	access	to	the	
actionable	business	 data	is	great.
— Simon Williams,CTO, Lemonaid Health
Working	in	a	rapid	environment	and	under	tight	deadlines,	quick	and	efficient	
delivery	is	essential	to	us.	To	that	extent	Knowi	has	provided	effective	dash-
boarding	solutions	 which	we	were	able	to	deploy	quite	quickly.	Setup	is	very	
easily	and	the	ability	to	connect	to	a	variety	of	databases	is	also	a	great	
advantage.	Moreover,	the	Knowi	team	has	been	prompt	in	providing	support	and	
a	clear	guidance	when	we	needed	it.	I	highly	recommend	Knowi	to	fellow	
startups.
— Hadar Shezifi, Co-founder, MKTMedia Stats
Datakwip provides	an	enterprise,	cloud-based,	 machine	learning	facility	analytics	
platform	collecting	streaming	data	for	facilities	across	the	globe.	 Knowi is	a	great	
partner	for	us.	 The	Knowi platform	enables	us	to	build	and	deliver	the	advanced	
IoT analytics	data	products	our	clients	need,	quickly.	 On	top	of	that,	the	Knowi	
support	team	is	excellent.	 They	are	always	there	to	help	us	when	we	need	it.
— Cory Purdue, CEO, DataKwip
Thank You

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Knowi Overview: NoSQL Analytics and Business Intelligence

  • 2. Data Stack is Changing to Enable Data- Driven Enterprises Descriptive Analytics Diagnostic Analytics What happened? Will it happen again? What should I do now? Mostly Structured Data Predictive Analytics Prescriptive Analytics Why did it happen? Blend of Structured, Unstructured, and Multi-structured Data Advanced Analytics Basic Analytics
  • 3. But…Traditional BI Tools are Stuck in the Past Only Understands Structured Data * Understands Structured, Unstructured, and Multi-structured Data + Machine Learning Understands Some Unstructured, and Multi- structured Data
  • 4. The Hidden Costs Of Not Understanding Modern Data Pre-define schemas Extract data using underlying query language Write custom code or use ODBC drivers or ETL to move data to relational tables 1 2 3 • Newer NoSQL data must be shoehorned back into relational structures • Forces duplication of data increasing cost of information and risk • Potential performance impacts when processing large datasets • IT teams must be involved to move and manipulate NoSQL data Adds months to projects Adds platform complexity Requires specialized resources Limits data discovery Changes are expensive Increased TCO
  • 5. Advanced Analytics on Modern Data Integrate Machine Learning Data-Driven Triggers Unified View of Enterprise Data Natively Understands Structured, Unstructured, and Multi-structured Modern Data Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics Native NoSQL Analytics
  • 7. Knowi Advanced Analytics Native NoSQL Integration •No ETL. No ODBC drivers. •Schema on read for instant data discovery Unified View of Data •Multi-datasource joins •Multi-structured nested datasets •SQL, NoSQL, RDBMS, API, CSV/JSON Native Query Generation •Drag & drop query generator •Integrated post processing •No specialize knowledge Integrated AI •Use built-in or bring your own Machine Learning algorithms •Data-driven triggers All Users Welcome Here •Technical and business users •Share, collaborate, and embed insights, print to PDF Enterprise Scale •Configure query execution to optimize for business use case •Cloud, OnPrem or Hybrid Deployment options
  • 8. Multiple Deployment Options • Queries are pushed down • Datasets are stored in Knowi Cloud Agent HybridCloud On Prem • Queries are pushed down to database • Data stays on premise • Agent accesses datasets for report generation • Everything is done on premise • Customer maintains server environment
  • 11. What Our Customers Are Saying Knowi helped Lemonaid in a number of ways to be able to quickly access critical business information from our secure HIPAA compliant data. Whether it’s for internal purposes or the partners, having very easy to use and quick access to the actionable business data is great. — Simon Williams,CTO, Lemonaid Health Working in a rapid environment and under tight deadlines, quick and efficient delivery is essential to us. To that extent Knowi has provided effective dash- boarding solutions which we were able to deploy quite quickly. Setup is very easily and the ability to connect to a variety of databases is also a great advantage. Moreover, the Knowi team has been prompt in providing support and a clear guidance when we needed it. I highly recommend Knowi to fellow startups. — Hadar Shezifi, Co-founder, MKTMedia Stats Datakwip provides an enterprise, cloud-based, machine learning facility analytics platform collecting streaming data for facilities across the globe. Knowi is a great partner for us. The Knowi platform enables us to build and deliver the advanced IoT analytics data products our clients need, quickly. On top of that, the Knowi support team is excellent. They are always there to help us when we need it. — Cory Purdue, CEO, DataKwip