Platfora Data Modeling

Platfora
Big Data Analytics for the Fact-Based
Enterprise

Mike Lee & George Komoto
Thursday, October 31, 13

What is Big Data Analytics?
Key Facts:

• Not deﬁned by size
• Hadoop is the leading framework
• Hadoop is open-source
Common issues

• Requires time and money to access data
• Many sources of data
• Quantity of data volume

Mike Lee + George Komoto

Platfora
Platfora transforms raw data in Hadoop into interactive, in-memory
business intelligence without the friction of IT or complexity of
existing approaches. A complete solution, it seamlessly connects data
to end-users. No separate data warehouse or ETL required.
The Challenge
Customers are getting stuck in the current stepped wizard approach.
The interface is not intuitive for non-database administrators.
The Solution
Design a graphical interface that permits creating multiple
connections in the same experience. The new workﬂow requires less
time to complete this task, and encourages more interactive
exploration and visualization of data.


Persona: Luis
Personas provided by Platfora


Persona: Marybeth
Personas provided by Platfora


Design Process
User Research

•

Gain more insights from typical end users (i.e. Tableau users)

•
•

Inquire about preferred tools and methodologies
Understand pain points in current workﬂows

Design Iteration

•
•

Present UI sketches to Platfora team for feedback
Test wireframes with target end users

•
•

General Assembly back-end engineers
Business/data analysts within network


Task Analysis: Deconstruct & Revise

Mike Lee ++ George Komoto
Mike Lee George Komoto

Select
Data Sources
(Linear Steps)


Select
Data Sources
(Linear Steps)

Connect
Data Sources
(Design Canvas)

Select
Data Sources
(Linear Steps)
Edit Data

Connect
Data Sources
(Design Canvas)

Platfora Task Analysis
Created By: Mike Lee
Date Created: 17-OCT-2013
Last Revised: 28-OCT-2013

Tasks
1. Select Data
2. Parse Data
3. Manage Fields
4. Create Reference
5. Key
6. Finish & Save

Login

Data Catalog

Data Catalog

Home

Click ‘Add Dataset’

Select target
dataset to view
details

Data Catalog

Select Data:
Choose source
data for dataset

Key
Screen

Action

[trees_SF]

Click ‘Add Dataset’

Click ‘Continue’

Display

Input

View reference
details in field

02:58

Decision

Loading…

Manage Fields:
Add computed
fields and verify
field info

00:00

Select Data:
Choose source
data for dataset

[species_SF]

Parse Data:
How to extract
rows and columns

My Datasets >
trees_SF

The complete task flow for
importing datasets, adding
references, and preparing for
Vizboards

[species_ID]

Raw file
contains
header?


Yes

Parse Data:
How to extract
rows and columns

Select column for
dataset join

Wrangled / Raw

Raw file
contains
header?

Click ‘Create
References’

Select checkbox


Yes

Select checkbox

Manage Fields:
Add computed
fields and verify
field info


Select column for
dataset join

Manage Fields:
Add computed
fields and verify
field info

Click ‘Create
References’

Click ‘Define Key’

Create
References:
Set up joins to
dimension dataset

Define Key:
Indicate column(s)
that make up the
unique key

Select target
dataset from
dropdown

[species_SF]

Select foreign key
from dropdown

[species_ID]

Select field(s) to
include in key

[id]

Click ‘Save & Exit’

[species_ID]

The task flow we are focused
on for this project.

Select target
dataset from
dropdown

[species_SF]

Select foreign key
from dropdown

[species_ID]

Name
reference?

Yes

Confirm?

Create
References:
Set up joins to
dimension dataset

Enter reference
name

“Species”

Click ‘Add’

“Species” appears
in References tab

Yes

Success message
popup

Click ‘Save & Exit’

Name
reference?

Confirm?

Yes

Success message
popup


Yes

User Research
Method
We conducted 7 interviews with people similar to our personas who
are currently using data analytics tools.
Findings
Access to data is a problem. Requests to make data warehouse
changes can take weeks. Preparation involves many schema and data
processing tools. The most common tool between stakeholders was
the data model diagram.
Opportunities Identiﬁed
Design a way to visualize and interact with the full data model.


Competitive Analysis: SAS


Competitive Analysis: Alteryx + Tableau


Competitive Analysis: Karmasphere


Ideation


Ideation: Onsite at Platfora


Early Wireframes


User Flow: Marybeth (Business Analyst)
1. Creates multiple links to a specific field from a different dataset that references additional data for
that row
2. Manages/edits references
3. Previews the content and see example data for each Fields
4. Identifies specific fields that can be used by another dataset to link rows back into that other dataset


1. Creates multiple links to a specific field from a different dataset that
references additional data for that row

Marybeth starts with the fact dataset. The key is already
selected. She uses the fly out menu to view her options.
She knows she needs to connect the other datasets in
the company catalog.


Platfora automatically lists the datasets in the catalog. It
also knows to match data types with the existing key.
Here Marybeth can link one or both target datasets.

2. Manages/edits references

Marybeth needs to make some changes to the reference
name. The ﬂyout menu she used to create the references
also has a link to make the changes she needs.


Marybeth edits the names of both of the target datasets.
Unchecking the boxes will remove the relationship.

3. Previews the content and see example data for each Fields

To quickly verify the datasets, the i button in the upperright provides a quick preview. To make changes,
Marybeth would have to explore the import/parse data
to make larger changes.


4. Identifies specific fields that can be used by another dataset to link rows
back into that other dataset

Similar to the original dataset she configured, when she
has more datasets, she can create references from target
datasets to other datasets.


Wireframe Feedback
Key Findings

•

Resolves the issue jumping back and forth within the import
data wizard, but still does not give a clear view of
relationships

•

Would require more development resources to create
because the components shown do not currently exist

•

Showing the relationships between the datasets should help
users avoid many of the issues they currently experience


Design for Humans: Interactive Web UI
Managing relationships between datasets should be as intuitive
and visual as working with Platfora Vizboards.
Design Language
How do we communicate the relationships between fact and dimension
datasets?
Visual Interface
How do we translate action steps into intuitive interactions?


Design Language: Entity-Relationship
Graphical user interfaces in
database administration is not
new. Several schematics exist to
represent relationships and the
ﬂow of data.

http://www.agiledata.org/essays/agileDataModeling.html


Potential Issues: Complexity & Overload


Visual Idea: Mozilla Collusion
(Star Schema)

(Entity
Relationship)

http://www.mozilla.org/en-US/collusion/demo/


Flow-Based Programming: NoFlo.js

http://bergie.iki.fi/blog/inspiration-for-fbp-ui/
http://noflojs.org/dataflow-noflo/demo/draggabilly.html
http://www.kickstarter.com/projects/noflo/noflo-development-environment


Prototype Link
Invision Link:
http://goo.gl/8wsVED


Thank You

GEORGE KOMOTO
UX Designer
@rgeorgek42


MIKE LEE
UX Designer
@mikejlee

Platfora Data Modeling

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