Wiseminer Informática Ltda offers a data intelligence and advanced analytics system designed to help businesses manage vast amounts of data and derive actionable insights. The software enhances productivity, efficiency, and decision-making, while addressing challenges such as fraud detection and analysis complexities. It focuses on empowering users with flexible, user-friendly tools for real-time analytics without the need for extensive programming skills.

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Make Smarter Decisions
Data Intelligence and Advanced Analytics System
Leonardo Couto
Associate Partner of Marketing and Sales
leo.couto@wiseminer.com
+55 21 9 7295 1422

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Big Data! Managing huge volume
of data and information to create value
6 Millions
Facebook pageviews
per minute
1.300
new mobile device users
per minute
US$2,8M
per minute of online global
sales (est. 2014)
20
new victims of identity theft
per minute
80%
of all world data are
unstructured
1 in 2
business leaders doesn’t
have access to the data they
really need
54%
of all corporates are using Big
Data software to gain a
competitive advantage
83%
of CIO’s have mentioned BI and
Analytics as part of their
visionary plan

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What problems do we solve?
● Simplify, accelerate and transform the data acquisition, integration and
link analysis process
● Improve the productivity and efficiency of IT, business users and
business intelligence team
● Provide detailed analytics outputs to support and improve the speed and
accuracy of business support decision process
● Reduce companies financial losses with advanced fraud management
systems and audit & compliance solutions
● Provide valuable insight that foster the creation of value and competitive
advantage
● Solve complex business problems that traditional BI tools cannot

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How do we solve it?
Data Intelligence is a rich and semantic way to deal with the raw data to
transform data into real value information. It is the capability to analyse various forms of
data in such a way that it can be used by companies to expand and improve their services
or investments. Companies can also apply data intelligence to analyze data of their own
operations or workforce, to improve productivity, and make better business decisions in
the future. Business performance, data mining, online analytics, and event processing are
all types of data that companies gather and use for data intelligence purposes.
Data Intelligence focuses in the data analysis, a much deeper view and understand of the
situation, than a traditional BI tools can deliver. Data Intelligence provide valuable insights
to improve companies business decision support and business strategy.

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Gartner: Advanced analytical
technologies are priority
"While the basic analytical technologies provide a general
summary of the data, advanced analytical technologies
deliver deeper knowledge of information data and
granular data.” - Alexander Linden, Gartner Research
Director
The reward of a smarter decision making process,
based on Data Intelligence, is a powerful driver to
improve overall business performance.
Source: http://cio.com.br/tecnologia/2014/10/29/tecnologias-analiticas-avancadas-sao-prioridade-afirma-gartner/
IT and business leaders must increase their efforts to
evolve from traditional BI tools, that focus on descriptive
analysis (what happened), to advanced analytical
technologies, that can answer questions like “why did it
happen”, “what will happen” and “what should I do”.
BI
Tradicional
Data
Intelligence

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The use of advanced analytical and Big Data
solution to prevent and detect fraud is still low
Global companies can lose up to 5% of their revenue due to fraud. The
use of advanced analytical solution for Big Data is a powerful tool to
combat fraud and corruption.
Source: "Big risks require big data thinking - Global Forensic Data Analytics Survey 2014", da Ernest & Young.
● 466 companies in 11 countries.
● High level employees.
● 72% believe that emergent big data
and analytical tools can play a key
role in fraud prevention and
detection.
● Only 7% are aware of any big data
and analytical technologies to
combat fraud.
● Only 2% are actually taking action and
using new technologies to reduce
financial losses with fraud, like FDA
(Forensic Data Analytics)
Four major points were described as
being challenges for companies:
● The access to the most suitable
analytical tool to do the job;
● Have the people with the knowledge
and skill to conduct analytical
interpretation and operate analytical
tools;
● The need of a complete review and
changes to improve business
process;
● The complexity and ability to
combine and conduct link analysis of
multiple type and sources of data.
The use of advanced analytical technology, and the real-time
analysis of data available, would have a direct impact on the
effectiveness of how they could synthesize and interpret the risks of
fraud and corruption in a timely manner to mitigate financial losses.

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To succeed in Data Intelligence project
you must focus on four pillars
People Knowledge Data (5Vs) Technology
Create value from data requires a lot of
talent, from the integration and data
preparation to construct databases of
specialized computing environments,
data mining and intelligent algorithms.
"Extract data value is not a trivial task"
says Linden. "One of the key elements of
any type program 'decipher the data' are
the persons who shall have the right skills
and capabilities".
Form a multi-disciplinary team with
business people, IT and other
professionals that are located in key
areas of your business.
"Knowledge must be improved,
challenged, and increased constantly, or
it will simply disappear" - Peter Drucker.
However, to improve and increase
knowledge and create insights, the Time
Intelligence solutions should be built on
top of clear requirements and goals of
the business areas, and that will generate
a competitive advantage for the
company.
Volume: what is the size of the database
to be analyzed?
Velocity: what is the speed and frequency
that data is generated or updated?
Variety: in which type and format the data
is available (related, tabulated, text files,
spreadsheets)?
Veracity: is this information real and the
source is reliable? Am I sure that this data
can be used for the company's to take
business decision?
Value: what is the real business value of
the data analyzed? Will it bring a
competitive advantage, or any other
improvement to the company's business?
The analytical tool must be:
Flexible and dynamic: to rapidly adapt
analytical model to consumers, clients and
market changes.
Reliable and safe: to give managers the
confidence to take business decisions,
timely and correctly.
Easy to deploy: fast and easy deployment,
requires less system and third software
integration. User interface friendly and
budget affordable.
Keep away from high complexity solutions,
known as “framework”. This requires lots
of system integration, tons of money, long-
term deployments, and often, long term ROI
(if any).
Make it simple and keep it simple.

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WISEMINER data intelligence software
WISEMINER is an end-to-end data intelligence software that enable
companies to:
● Capture: Any sort of data. Transactions, interactions, opinion, data logs, ...
● Analyse: Transform and enrich the data using the graphical and intuitive data
flow and data modelling (Link Analysis) interface.
● Predict: Create predictive analytics model based on consistent business rules
and neural network. Create real time and predictive alerts based on a
sophisticated classification and scoring engine.
● Act: Customized dashboards for business decision support. Ad-hoc
changes of data modelling, business rules, classification and scoring enable the
business analyst rapidly adapt the whole data model accordingly to any
changes in the market, in competition, customer behaviour or any changes that
may impact the business decision process.

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ANALYSE
Transform and Enrichment
PREDICT
Analyse and Predict
ACT
Smarter Decisions
CAPTURE
Identify and Capture
How does WISEMINER works
Social Network
Financial, market,
industry indicators,
any data
Customer data
(i.e. CRM)
Data transactions
Data
Integration
Data
Exploration
Link Analysis
Data & Text
Mining
Social Network
Analysis
Data Transformation
and Enrichment
Data Modelling,
Entity Relationship
Model
Statistical
Analysis
Business Rules Neural Network Classification and
Scoring
Data Visualization
and Dashboards
Process Automation
and Scheduling
Management and
improve
Business Decision
Support System
Regression
Analysis
Predictive Modelling
Risk Management
Alarm and Alert for
Fraud, Deviation and
Compliance
Competitive
Advantage

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The problems with traditional BI, in-house
and analytics framework solutions
Little or none
flexibility
Less flexible database with predefined and specific layouts to capture and load the data.
Changes are complex, timely and costly. Requires highly skilled professionals and consultants,
a whole new project and other tons of money!
Expensive
Long ROI
Less Results
Long term implementation of business intelligence project tend to become obsolete very fast
as the market changes are more dynamically and, most of the time blows out the budget. As
much of systems integration, programming, customized development and softwares are
needed to solve a business problem, more expensive it will get and forget ROI !!!
Complex to
Use and
Manage
Non user friendly, and complex implementation (such as frameworks) are not easy to use and
manage. Requires highly and experienced skilled professionals with programming and
statistical knowledge to use and manage the solution with the minimum efficiency.
Due to the high costs, and the complexity, of business intelligence and advanced analytics solutions in the
market, many companies are investing time, resources (people) and money to create their own in-house BI and
analytics systems. It may be based on database queries, macro-powered spreadsheets, or even using old tools
like MS Access. But, this systems has many things in common. Lack of security, high costs to maintain, no
programming documentation, lack of support and it doesn’t evolve. Usually it is replaced and becomes a legacy
system.
In-House
Solutions

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What differentiates WISEMINER
Flexibility
● Designed to increase the business analyst productivity and respond to any
business needs.
● Incremental, ad-hoc, dynamic data modelling to rapidly respond to market
changes and business needs.
● No programming needed, at all !!!
End-to-end
● Support multiple files format and different database sources.
● Link analysis, data integration, predictive analytics, classification and scoring, all
you need in one user interface.
● Customized dashboards to answer the needs of many business analysts and
decision makers.
● Automate and schedule any system task, accordingly to business needs.
● Create and monitor real time alert for fraud, process deviation and corruption.
Fast ROI
● Easy to install and integrate with existing databases and legacy systems.
● No programming needed requires less resources, less people.
● Easy data integration reduces the need of developing in-house systems to solve
business problems. More secure, controlled and optimized systems.
● Easy to use, friendly user interface.
● We deliver the answer to business problems on-time and on-budget !!!

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Backup
Maybe too tech!
*system screenshots in portuguese*

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Data load and integration
System screenshot

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Data Exploration and Enrichment
System screenshot

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Data Transformation and Enrichment
Example of an e-commerce analysis
Data Model - Data Entity
User
Shopping
Driver
License ID
Product
Address Zip
Phone
Number
IP Address
Credit
Card
Number
Users
Shopping
transaction
External Data

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Data Entity - Explore N possibilities
Example of an e-commerce analysis
Data Entity
Related Data
Fields
● Insights
● Statistics
● Aggregations
User
Shopping
Driver
License ID
Product
Address Zip
Phone
Number
IP Address
Credit
Card
Number
How many users
used the same IP
address?
How many users
informed the same
phone number as
customer contact?
What was the
total value of a
transaction?
This same credit card
number was used before to
buy products with different
delivery address?

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Visualization and Dashboards
Customized to answer business needs

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Classification and scoring based
on business rules and predictive model
Scoring
Business
rules
Multiple business rules defined by business
analysts that, when grouped together, will
create the final scoring
May represent:
Risk
Compliance
Quality
Classification
Etc…
How it works:
Predictive
model
Based on neural networks and decision tree
algorithms trained using the historical data
stored for regression analysis

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Creating the historical data repository
“Data Images”
Data Data' Data'' Data''' Data''''
Image
1
Image
2
Image
3
Image
4
PresentPast
Very useful to analyse customer behaviour, credit concession, fraud and corruption behaviour, prevent and detect non-
compliance operations, and compare other historical data with present information.

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Task automation and scheduling

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Manage, event log and problem determination

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System architecture
WISEMINER Service
ModeloModeloModel
Data Entities
Data Images
Connections
Tasks
Jobs
Task Manager
Analytics Engine
Database
Apache Tomcat
Wiseminer Web
Java Web Start
Wiseminer Studio
● Exploration
● Management
● Dashboards
● Analyst Interface
● Data Load
● Data Modeling
● Explore Data and
Entities relationships
● Data Analyst or
Statistical
System
Files

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Supported Platforms
IBM
z/Linux
IBM IFL (Integrated Facility for Linux)
SuSE Linux Enterprise Server 11
Java 7
PostgreSQL 8.4
Intel or AMD microprocessor
Windows Server 2003 / 2008 / Linux
Java 7
SQL Server / PostgreSQL / Oracle Database
IBM Power 7 / 7+ / 8
Red Hat Enterprise Linux 6
Java 7
PostgreSQL 9.2
Supported Platforms - WISEMINER v4
Clouded or Hosted Services

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Thank you
For more information about Wiseminer
please contact us:
info@wiseminer.com
+55 21 2711 4359
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