Hooduku Inc claims to provide solutions for big data needs through implementing tangible technical and business solutions. They have over 50 years of combined experience building enterprise systems for companies like Amazon and Microsoft. They can help customers configure and deploy technologies like Hadoop and Pig to analyze large datasets and provide actionable insights. They provide a case study of implementing a big data solution for a Houston-based natural gas company to acquire pipeline data through SCADA systems and analyze it with Hadoop and SQL Server. They describe how big data analytics could help a retailer like Acme Inc. predict hot products, customer demand patterns, and offer personalized promotions to drive sales.

1. Hooduku Inc
We refined SaaS!
“SaaS is Solutions as a Service and not just
Software as a Service”
We can help solve
missing puzzles
with your Big data
needs
We know Big data and have implemented solutions for customers and
not just proof of concept solutions
PS: ACME is a fictional organization. Real customer name cannot be shared due
to NDA

2. Summary
• Over 50 years of combined techno-functional
experience building enterprise systems and
products for companies like Amazon, SeeBeyond
(Oracle), HP, Microsoft, several startups and
industry verticals such as Baker Hughes,
EaglerockEnergy&AmericanMidstream, CISCO
&Netgear
• Background and experience building enterprise
application integrations, Systems integration,
Data mining, Big data analytics , Data
visualization products and solutions
How can we help?
• We can help you with implement best
in class Big data solution to improve
your ability to reaching out to
customers quickly, be competitive
from both costs and product offering
and orchestrate a smarter inventory.
Skills & Expertise
Agile
Methodologies/Project
Management
Big Data (Hadoop)
Building large scale ETL
tool – Retail & Finance
Batch Processing/Real
time processing
leveraging Hadoop Map
Reduce/Storm
Big Data for Retail
IndustrySpecialization
•We specialize in providing tangible technical/business solutions, which impacts
employee/staff productivity and customers measured immediately, but will deliver
substantial returns gradually over 3-6 months or longer.
• The fees we charge are by far the best in the industry considering the vast industry
experience we bring to the table.

3. Hadoop/Big data
• In year 2006 – built a verticalized search engine for
employers and job seekers. The Nutch Search engine was
customized to provide the search capabilities.
• Hadoop clusters were used to run parallel job crawlers and
custom crawlers.
• Drupal CMS was the front end to show filters and search
results.
• Project was shelved in 2007, since the idea was new and
lack of funding.
Xervmon: Cloud Cost Management analytics
• Leveraged HadoopClusters to run map reduce jobs to
execute projection algorithm and store real time cost
projections in shardedmongodb in order to scale projections
on large data sets
• Helped Build data visualization charts leveraging D3 and
Google Charts leveraging LAMP Stack – custom app.
• Currently extending the architecture to support Graphite DB,
Hadoop and mongodb to support System and application
perf. stats.
• Built a home grown data collection engine to support
multiple cloud providers such as Amazon AWS, Rackspace
Cloud, HP Cloud, Softlayer and several ISPs such as
Timewarner and Comcast.
• Helped build home grown Analytical framework to project
costs on dynamic costing scenarios for Cloud within in SME
segment.
• Currently team is executing plan to provide enterprise grade
turn key cloud management solution.
Big data technologies allow you to deal with massively large data
sets. Common applications are meteorology, genomics,
connectomics, complex physics simulations, biological and
environmental research, Internet search, finance and business
informatics.
Technologies like Hadoop, Pig, Hive, R and many others are there
to help you overcome limitations of capturing, storing, search,
sharing, analyzing and visualizing of large datasets.
We can help you configure and deploy such technologies to suit
your particular needs.
Mobile Apps
• We have developed several apps for Apple and Google Play devices.
• Several apps developed by us is available onItunes or Google Play store.

4. Case study: Big Data in Houston based company
Customer sources natural gas and distributes to
customers.
The Client owns and operates
pipelines in gulf coast
Apart from measuring equipments, SCADA
(supervisory control and data
acquisition)
and Flow cal is implemented for
1. Data acquisition over AMS network
2. Natural gas measurements.
P1
P2
P3
Oil Inbound streams
G1
G2
SQLServer1
G3
SCADA
/
FlowCAL SQLServer2
Cluster Sharepoint
Business
Intelligence
Job1-Jobn
Job -1 – n are batch jobs
Sourcing data from ODBC
compliant DB and dumping
into SQLServer Cluster
Reporting and business
analytics apps are written to
be accessible via Sharepoint
Portal and mobile devices
Reports on the Go
For business folks

5. Potential Big data - Retail Solution
• Busiest shopping time of the year
– and one video game is flying off the shelves.
– Retailer reacted quickly to this demand has the advantage
Source Historical data
Enterprise
Data
Loyalty
Programs
Social
Media
Web
Browsing
Patterns
Preparing for future demand. Predicting trends
and preparing for future demands
A Retailer Acme wants to
be retail leader
Predict hot items for the season
Combine data with
relevant information
Analytics 0%
50%
100%
Dockers
Jockey
Calvin Klien
Create models of trends – leading products, brands &
categories

6. Enterprise
Data
Loyalty
Programs
Social
Media
Web
Browsing
Patterns
Analytics
Customer
Transactions ($/£/€/¥)
Local Buzz
0
5
Mid
West
West
Coast
East
Coast
South
West
Demographic Data
Asians
Americans
Spanish
Research Data
Shopping
Patterns
Predict areas where demand is highest
Brick & Mortar
Online

7. Actionable Insights derived from Bid data analytics
Trends of hot products, brands and
categories
Predict areas of demands
Stock up and deliver the products
for which demands exist across
 Brick and Mortar locations
 Online (Location aware through
consumer traffic online – so stock up
in distribution center closest to
customer.
 Products
 Categories
 Brands
Demand /Activity/Value
Customer
Demand
Competitor
Activity
Shareholder
Value
$39.99
Derive price optimization models
Real time analytics to synchronize prices hourly
with demand inventory & Competition
Customer
Demand
Competitor
Activity
Shareholder
Value
Acme’s Price

8. Pinpoint & Segmentation
Enterprise
Data
Loyalty
Programs
Social
Media
Web
Browsing
Patterns
Analytics
Social Media
Forums
Customer
Loyalty
Browsing
Patterns
Demographic
Data
Segment customers according to
expected buying behavior
Drive customers
to nearest Kohls
if they are in
right direction
Engage customers with
personalized real time offers
Pre order
popular
items
Spend
and earn
gift cards
$15 off
exclusive
bundle

9. How can we help?
• Hooduku can set up best in class Big data
infrastructure to
– Perform deeper analytics on all data
– Find meaningful patterns and hidden insights
– Help Acme Inc to use the insights to create best
shopping experience and influence purchase decisions
to their customers and edge out competition
Out of stock
Anticipate demand
Availability at right location
Dynamic Pricing
Relevant Promotions
Timely offers
10% higher
price

10. Q & A
• Thank You
Partial Clients
• WE help y