Data Blending, Caching and Optimizing

Data Blending, Caching and Optimizing

Alma Martin

#Logi16

ALMA MARTINProduct ManagerLogi Analyticsamartin@logianalytics.com

Here is an interesting fact about myself few people know.

ABOUT ME

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#Logi16

► The Data Problem

► How Logi addresses the Data Problem

► Logi DataHub Overview

WHAT WE ARE GOING TO LEARN TODAY

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The DATA Problem

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Data is often the biggest challenge of self-service analytics

Preparing Data for Analytics is Hard

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#Logi16

The Data Problem in Self Service Analytics

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Data lives in different places.

Organizations outsource applications to run their business (e.g. CRM, Sales, Marketing)

Accessing Data

RDBMS Applications Files

Half of the organizations are accessing external data sources*

*MQ Survey for BI and Analytic Platforms

#Logi16

The Data Problem in Self Service Analytics

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Data lives in different places.

Organizations outsource applications to run their business (e.g. CRM, Sales, Marketing)

Accessing Data

RDBMS Applications Files

Transactional systems are often not ready for analysis.

Need to blend data across sources to get a 360° view of the business.

Acquiring Data

RDBMS Applications Files

#Logi16

The Data Problem in Self Service Analytics

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Data lives in different places.

Organizations outsource applications to run their business (e.g. CRM, Sales, Marketing)

Accessing Data

RDBMS Applications Files

Transactional systems are often not ready for analysis.

Need to blend data across sources to get a 360° view of the business.

Acquiring Data

RDBMS Applications Files

Data needs to be refreshed and up to date for reporting.

Accessing and reporting on data in a performant experience.

Managing Data

RDBMS Applications Files

OUR SOLUTIONLogi DataHub

Connect and acquire data, including files, databases, and cloud applications

Create, prepare, and manage dataviews for self-service analysis

Speed data prep with smart profiling, joining, and data enrichment

Accelerate performance for large data sets with a self-tuning, easy to maintain columnar data store

@soulety

Connect

• Applications

• Databases

• Files

Data Connectors

Author

• Joining objects

• Blending data sources

• Filter objects

Dataview Authoring

Cache

• Columnar store

• Self-tuning

• Scheduled refresh

Data Repository

Prepare

• DataSmart profiling

• Calculated columns

• Multi-part text

Data Enrichment

… For Self-Service

• Element in Logi Studio

• Info, SSM, Discovery

• Columnar store for Vision

Logi Integration

Create and Manage Dataviews

@soulety

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Primary DataHub Use Cases

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1

2

3

4

Offload transactional systems that are not optimized for analysisEnsure transactional system is not overloaded with analytical requests

Blend data from multiple sourcesCombine data from databases, applications and files into a single dataview

Support application data sources not included with Logi InfoExtends self-service analysis (SSM) to application sources

Create and manage dataviews for self-service analyticsSelf-managed data repository that does not require DBAs to administer

#Logi16

Primary DataHub Use Cases

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1

2

3

4

Offload transactional systems that are not optimized for analysisEnsure transactional system is not overloaded with analytical requests

Blend data from multiple sourcesCombine data from databases, applications and files into a single dataview

Support application data sources not included with Logi InfoExtends self-service analysis (SSM) to application sources

Create and manage dataviews for self-service analyticsSelf-managed data repository that does not require DBAs to administer

#Logi16

Offload transactional systems from analytical requests

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Info Analytic Application

Transactional Application

Data is optimized for transactions

(inserts / updates)

Data is optimized for reporting and analysis

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Offload transactional systems from analytical requests

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Franchise Management Software

Transactional system overloading concerns with self service reporting.

Healthcare Solutions

Managed and self service solutions that require isolation of the

transactional system.

#Logi16

Primary DataHub Use Cases

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1

2

3

4

Offload transactional systems that are not optimized for analysisEnsure transactional system is not overloaded with analytical requests

Blend data from multiple sourcesCombine data from databases, applications and files into a single dataview

Support application data sources not included with Logi InfoExtends self-service analysis (SSM) to application sources

Create and manage dataviews for self-service analyticsSelf-managed data repository that does not require DBAs to administer

#Logi16

Blend data from DBs, Cloud Applications, and Files

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Sales & Marketing Files

OFX

DatabasesFinance / ERP

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• Salesforce Connect

In App Data Blending Solutions Are Limited

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Connects Salesforce data to external sources ✓Recommended for big (external) datasets Follows security rules defined by the company Generates reports and charts from blended data External data can be used in formulas

#Logi16

Primary DataHub Use Cases

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1

2

3

4

Offload transactional systems that are not optimized for analysisEnsure transactional system is not overloaded with analytical requests

Blend data from multiple sourcesCombine data from databases, applications and files into a single dataview

Support application data sources not included with Logi InfoExtends self-service analysis (SSM) to application sources

Create and manage dataviews for self-service analyticsSelf-managed data repository that does not require DBAs to administer

#Logi16

Extended Support for Application Sources in Info

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Info Supported SourcesDataHub Supported Sources

#Logi16

Primary DataHub Use Cases

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1

2

3

4

Offload transactional systems that are not optimized for analysisEnsure transactional system is not overloaded with analytical requests

Blend data from multiple sourcesCombine data from databases, applications and files into a single dataview

Support application data sources not included with Logi InfoExtends self-service analysis (SSM) to application sources

Create and manage dataviews for self-service analyticsSelf-managed data repository that does not require DBAs to administer

#Logi16

Self-managed data repository that does not require DBAs to administer

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• No need to tune/index DB for self-service demands

• Minimal involvement from DBAs

• Faster deployment

Using Logi DataHub

#Logi16

Data Authoring in 5 Steps

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1.Create a Source

2.Build your Dataview

3. Enrich your Dataview

4.Define a Data Refresh Schedule

5.Connect to Logi Info

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1. Create a Source

Establish data connectivity

Applications Databases Files

OFX

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2. Build a Dataview

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Define and cache an optimized table that blends data across sources

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3. Enrich your Dataview

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Create calculated columns, adjust column names and types, etc.

New Col 1

New Col 2

New Col 3

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104105106

ID100101

103102

4. Schedule Data Cache Refresh

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Full Replace or Incremental Append

Source Data DataviewID

100101102103

104105106

ID100101

103102

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4. Schedule Data Cache Refresh

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Full Replace or Incremental Append

DataviewID

100101102103

104105106

ID100101

103102

Source Data

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5. Connect to Logi Info

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Use Dataviews for Self Service reporting and custom Logi Apps

Interactive Dashboards & Reports Data Analysis SharingData Query AuthoringDiscovery

BRINGING IT ALL TOGETHER

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Logi Analytics for Self-Service

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Learn more with the Gartner 2016 Critical Capabilities Report for BI and Analytics Platforms