Research2

BI Front Ends, the “Face” of Analytics

 

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What’s Our Focus This Week?

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Back End

(Storage)

Extract, Transformation and Load

(ETL)

Front End

(Projection)

 

+

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Self Service BI = Nirvana

No IT involvement, users are empowered to access and analyze data themselves

 

No pipeline of requests, no delay

 

Change occurs at the pace of business

 

 The reality is different due to staffing, complexity and skill level

3

Source: Howson

Self Service BI

Data Scientists

“Play” Here

IT Creates

Semantic

Layer

IT Creates

Semantic

Layer

IT Develops

IT Develops

4

Source: Howson

Business Query and Reporting Tools = Ad Hoc Query Tools = Self Service Access

Allow business people to create queries without having to know SQL

 

Business user builds the report, not IT

 

Business can’t wait, so they

Either demand their own environment supported by IT or

“Go it alone”

 

True ad hoc = a one time effort. What are often called “ad hocs” by the business are really production reports they can’t live without

 

BI is iterative so these “front end” display projects tend to be Agile while “back end” data loading and cleansing projects tend to be waterfall (more on this later in the course)

5

Source: Howson

What Makes A Report? Formatting…

Standard reporting templates are important for corporate look and feel

 

Font style, conditional formatting

 

Cross tab, chart, master – detail

 

Complex: multiple charts on a page

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Comparison: Predefined and Ad Hoc Reports

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Source: Howson

The Semantic Layer = The Business View

Uses business terminology vs. physical field names

 

Automatically connects related tables via SQL joins

 

Provides metrics that calculate and aggregate facts

 

Up front investment yields good ROI:

Consistency

Lower maintenance

Higher accuracy

8

Building the Semantic Layer and Reporting

 

Step 1: Import the Data Structure

Step 2: Design the classes and

objects:

Step 3: Implement the semantic

Layer

Step 4: Users build queries with the

query panel

Step 5: Users generate reports

(users from IT or business)

Source: SAP Business Objects

Note: These screens show

the development flow

and are not related

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Challenges

Since BI tools are the “face” of BI they get an inordinate amount of attention. Users see the tools so they will blame them for any problems

 

Ad hoc reports developed by the business tend to be more robust and effective than those developed by IT. Unfortunately, IT doesn’t know about them!

Most of the time, IT leaves it to the business to test “ad hocs”

Good idea: Open dialog to “productionize” the business’ “ad hocs”

 

Without a clear strategy, static reports become redundant with both themselves and ad hoc reports

Consider a report rationalization effort to consolidate and achieve a single version of the truth for each predefined report. Publicize this with the business to save on their “ad hoc” production reports

 

When users “go it alone” they usually run into scalability issues and IT is pressed into service at the 13th hour to take on support

 

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Challenges (Continued)

Make sure you design a semantic layer that is intuitive to the business community (surprisingly, this often does not occur!). If not you risk:

Rejection

Inaccuracy

Perception of failure

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Visual Data Discovery

This niche is growing at three times the pace of the overall BI market. It is evolving and not yet well defined

 

Visual data discovery is “…a tool that speeds the time to insight through the use of visualizations, best practices in visual perception and easy exploration (Howson, 2014)”

 

Users may not know what they’re looking for until they navigate and drill within a data set for details and trends

 

Visual discovery tools may lack the business metadata layer and tabular data sets characteristic of business query tools

 

Provides agility and ease of data access and insight

 

 

 

12

Source: Howson

Comparison: Business Query and Visual Data Discovery Tools

13

Source: Howson

Example: Tableau Visualizations

https://public.tableau.com/en-us/s/gallery

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Let’s check out Tableau Public:

Dashboards

Like car dashboards

 

Present information from multiple data sources

 

Present multiple numbers in different ways

 

Include highly visual indicators and/or reports

 

Business users want to customize their own dashboards with relevant information

 

Some dashboards, like those sourcing operational information directly, require IT support

 

15

Source: Howson

Dashboard Example

Production Reporting

Static reports with sophisticated formatting and design

 

Also known as:

Pixel perfect reporting

Operational reporting

Enterprise reporting

Canned reporting

Predefined Reporting

 

May access operational systems directly, an operational data store or detailed data in a data warehouse

 

Developed for:

Avoiding “run away” queries

Embedding within a transaction system (i.e. inventory levels, bill of materials, invoices, etc.)

Presenting common enterprise requirements

Static reporting (Example: Reinsurance statutory reporting)

Management reports by IT in lieu of available production reporting tools

17

Source: Howson

Example: A Bad Production Report

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Comparison: Production Reporting and Business Query Tools

19

Source: Howson

The Case of the Production Report vs. Business Query Debate

IT recommended batched production reporting for preprocessing and availability via SAP Crystal Reports

Driven by concerns about data volumes and load times

Users were accustomed to static reports and IT concluded they still wanted that

With predefined reports, each report would needed to be developed, replicated, then maintained

 

Users then requested the templates used to create these production reports to be made available for querying and ad hoc report (i.e. “shadow production report”) development, so SAP’s Business Objects Web Intelligence was used

Concerns about “pixel perfect” were addressed: both tools satisfied the need

Concerns about rendering and data load were not resolved, though preprocessing was available via the Business Objects administrator

Semantic layers could be shared

 

A huge, extended dialog ensued where we decided to create and reuse templates (Prof saw that coming on the first day of the discussion)

 

 

 

 

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The Argument

21

Source: Howson

Mobile BI

Similar to the internet, mobile is ubiquitous, someday it won’t be “special”

 

For now, the mobile BI challenge remains unique:

Design for small and varying screen sizes

Bring Your Own Device (BYOD) introduces managerial and security challenges

 

The user experience with browser based access is not optimal, native device-based apps should be used for accessing, authoring and viewing content

 

22

Source: Howson

BI and Microsoft Office

Unofficially the leading BI tool (good for Microsoft!)

 

Wreaks havoc on BI’s goal of providing a single version of the truth

 

The preferred user interface

 

Need to facilitate integration while managing use

Old: Export from a managed environment to an Excel spreadsheet. The result was chaos

New: Most vendors integrate with Excel to extend BI’s reach

 

Office 2016 includes visualization and in-memory processing

 

 Exporting data to Excel spreadsheets is not BI and is dangerous, managing Excel use to explore data is beneficial

 

23

Source: Howson

Reference List

Howson, C. (2014). Successful business intelligence: Unlock the value of BI and big data. New York. McGraw

Hill Education. ISBN: 9780071809184

 

www.tableau.com

 

 

 

 

 

 

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