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BI, Analytics and Big Data A Modern-Day Perspective By: Elad Israeli, Co-Founder, SiSense http://www.sisense.com

What is bi analytics and big data

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Define what is Business Intelligence, what is Big Data and the differences between them.

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Page 1: What is bi analytics and big data

BI, Analytics and Big Data A Modern-Day Perspective

By: Elad Israeli, Co-Founder, SiSense

http://www.sisense.com

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Business Intelligence (Analytics)

A set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information for business purposes.

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This is a Report (= a query)

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This is a Dashboard (= several queries)

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…and BI/Analytics is:

The ability to create a new report, dashboard or just get a new analytic question answered in real-time, or

at least in-time.

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What is Big Data?

A collection of data sets so large and complex that it becomes difficult to process using on-

hand database management tools or traditional data processing applications

Due to its technical nature, the same challenges arise in Analytics at much lower volumes than

what is traditionally considered Big Data.

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..so Big Data Analytics is: The same as ‘Small Data’ Analytics, only with the

added challenges (and potential) of large datasets

(~50M records or 50GB size, or more)

Challenges, such as:

• Data storage and management

• De-centralized/multi-server architectures

• Performance bottlenecks, poor responsiveness

• Increasing hardware requirements

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BI and Analytics Projects

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Approaches to The Challenge

1. Project-Specific:

– The development of a specific dashboard/report

– An isolated initiative, with no forward-looking implications from the prospect’s perspective

2. Solution-Oriented:

– The development of a specific dashboard/report, with future ones (known or unknown) in mind

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E.K.G: Solution-Oriented vs. Project- Specific

Time

New Report New Report

BI/Analytics (Solution-Oriented)

Time

New Report New Report New Report

Report/Dashboard Project (Project-Specific)

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BI/Analytics E.K.G

Time

New Report New Report

The rate at which new reports are introduced into critical processes should increase over-time, due to: • Completed integration, customization & adaptation • Time for training to sink in • Adoption (more users generating reports)

New Report = Answer To New Question = New Insight

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How Raw Data Becomes Insight

Connect To Source

Load & Store

Clean & Standardize

Grant Access

Define Queries

Format The Report

Share the Report

Respond to Feedback

ETL / Data Management

BI/Analytics/Visualization

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Data Warehouse

• Clean and accurate data recognized as the only real business ‘truth’

• A central repository of data which is created by integrating data from one or more disparate sources

• Stores current as well as historical data

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Existing Data Landscapes

Owner: IT

Owner: IT or Business

DW

• The data is in its detailed form (raw data) • The data is located in multiple places • The data may be dirty (i.e. entry-errors) • The data is accessible to whoever owns

the application/database • The data is not centralized

With an existing Data Warehouse Without an existing Data Warehouse

• The data is in its detailed form (raw data) • The data clean (was already processed) • The data is usually only directly accessible to IT • The data is centralized (single version)

Operational DB Application DB Files

Operational DB Application DB Files

ETL

Data Marts or OLAP Cubes (optional)

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Traditional BI/Analytics Architectures

(Old-School)

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Traditional BI/Analytics Architectures

End-Users (Business) End-Users (Business)

Detailed Dirty Unstructured

Centralized / Data Warehouse Non-Centralized / No DW

Summarized De-centralized Clean Structured

Detailed Dirty Unstructured

Detailed Dirty Unstructured

DW

Data Marts or OLAP Cubes

Owner: IT

Owner: IT or Business

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Traditional Architectures - Comparison

Centralized / DW Non-Centralized / No DW

Approach Solution-oriented Project-specific

Data Quality & Accuracy Higher Lower

Scalability Higher Lower

Single Version of the Truth Yes No

Initial Investment Higher Lower

Level of Detail Summarized Granular

Owner IT IT or Business (optional)

Implementation Time Longer Shorter

Technical Complexity Higher Lower

Advantage / Disadvantage

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Modern-Day BI/Analytics Architectures

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Modern-Day BI/Analytics - Focus

• Self-Service

– Empower business users of varying skill-levels

– Keep IT in control, without becoming a bottleneck

• Agility

– Fast turnaround for new requirements

• Scalability

– Handle large, or rapidly growing volumes of data

– Handle fast, unpredictable usage patterns and adoption

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Modern BI/Analytics – How?

• Full-Coverage Solution

– Provide all functionality required, from data management, ETL and end-user analytics

• Utilize modern technology

– Columnar databases

– In-Chip analytics technology

– Support for 21st century chip-sets

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Architecture: With a Data Warehouse

End-Users (Business)

Detailed Centralized Clean Structured

Detailed Dirty Unstructured

DW

Owner: IT

End-Users (Business)

Summarized De-centralized Clean Structured

DW

Marts or OLAP Cubes

Owner: IT

Modern Traditional

ElastiCube

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Modern vs. Traditional (DW) Centralized / DW SiSense Architecture

Approach Solution-oriented Solution-oriented

Data Quality & Accuracy High High

Scalability High High

Single Version of the Truth Yes Yes

Initial Investment Higher Lower

Level of Detail Summarized Granular

Owner IT IT or Business (optional)

Implementation Time Longer Shorter

Technical Complexity Higher Lower

Advantage / Disadvantage

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Architecture: Without a Data Warehouse

End-Users (Business)

Detailed Centralized Clean Structured

Detailed Dirty Unstructured

ElastiCube

Owner: IT or Business

End-Users (Business)

Owner: IT or Business

Detailed Non-Centralized Dirty Unstructured

Detailed Dirty Unstructured

Modern Traditional

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Modern vs. Traditional (No DW) Non-Centralized / No DW Modern Architecture

Approach Project-oriented Solution-oriented

Data Quality & Accuracy Lower Higher

Scalability Lower Higher

Single Version of the Truth No Yes

Initial Investment Lower Lower

Level of Detail Granular Granular

Owner IT or Business (optional) IT or Business (optional)

Implementation Time Short Short

Technical Complexity Lower Lower

Advantage / Disadvantage

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You Can Get Modern BI/Analytics Today!

Schedule Your Free Demo Now!

http://pages.sisense.com/demo-request.html