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Archive for the ‘White Papers’ Category

Cognos Active Reports

By Itzik Maoz, Director of Business Analytics Practice for Creative Computing, Inc.

One of the most rewarding aspects of teaching students about Cognos Business Intelligence is to witness their enthusiasm when they grasp the software’s possibilities and power. They don’t need to be IT professionals to learn how to extract vital information, analyze it and create meaningful reports.

I’m especially excited about Cognos’ ability to produce active reports. This unique format lets you create dashboards for a comprehensive view of multiple aspects of your vital information, and you can see it on your tablet, Android smart phone or computer. You can also run active reports in a variety of browsers. You get information right when you need it, even if you are not connected to the Internet or your network, so that you – or your customers – can make informed decisions.

With Cognos’ active report feature, the information is presented in a very dynamic way. The active reports let you use a variety of interactive prompts and charts, including bubble charts, trend Chart, etc. You can view different types of information, such as sales by region or by product, on one dashboard. There are so many options; it’s easy to customize the reports.

You can also quickly process information in an extremely visual way, especially if you’re using IBM’s Rapidly Adaptive Visualization Engine (RAVE), which makes the visualizations interactive and animated. It’s not just a static report. It visually changes, moves and shifts on command. For example, you can visually observe how your different product lines shift as you slide the time slider with your finger on your iPad.

Create and Interact
In a LearnQuest class, we talk about how to create active reports and how to interact with them. It’s a combination of demonstrations and hands-on work. We discuss the features and the concepts. Students practice using sample data – typically sales data because it’s easy to understand.

Before taking any Cognos class, it helps tremendously if you review the prerequisites. You’ll simply get more out of the class, if everyone enters at the same level.

I’m a trainer in these sessions, but I can also share my knowledge as a consultant and a frequent user. I help people understand how the software relates to the student’s industry or their job. Cognos is used in all industries and at all organization levels. My students are from a variety of industries, with the majority of them from the Finance and Sales departments.

Sharing my knowledge is part of my personality. Showing people how to get the most out of this great technology so they can grow their company gives me a lot of satisfaction.

About the Author
Itzik Maoz is Director of Business Analytics Practice for Creative Computing and has more than 15 years of Business Analytics experience. Based in Providence, R.I., he has worked with many of New England’s most recognizable companies in Manufacturing, Retail, Healthcare and Higher Education. He is proficient in the entire IBM Business Analytics stack and is well versed in the entire Business Analytics project lifecycle.


The Buzz in Big Data

By Itzik Maoz, Director of Business Analytics Practice for Creative Computing, Inc.

Who doesn’t want more insight? Instead of looking in the rearview mirror for analysis of what has happened, many companies now want to be able to look forward, understand what they see and predict what’s going to happen next with an increasing degree of confidence.

Together with a rapidly increasing volume of data, they’re looking at “Big Data” technology for answers.

Big Data is the new buzz phrase. You can hear it all around you and make an impression just by dropping words like Hadoop, Netezza, MapReduce, NoSQL, etc…

But how big is big? When does an organization move to these platforms? Can you effectively analyze and predict, using your current databases and infrastructure? The answer is “absolutely yes.”

You don’t necessarily have to have a Big Data platform in order to make good predictions and play the analytics game. Many companies can still make business cases and decisions based on the information in their existing databases.

What are the types of skills that you need? Do you need to hire Ph.D.s, statisticians and rocket scientists? Not necessarily.

Though the skillset of the “data scientist” is emerging in the industry, your own bright analysts and BI/BA teams can be successful with finding patterns in data and making predictions.

IBM SPSS Modeler is one example of an application that takes the mystery of advanced statistics and helps your team get results. With the integration with your BI Platform, especially IBM Cognos, it is easy to communicate and present your findings and recommendations so that executives can visualize and make sense of your analysis, gaining insight and triggering action.

Next time I’m going to write about types of analysis that companies use to gain competitive advantage — and that some organizations use to better the lives of people in the community.

About the Author
Itzik Maoz is Director of Business Analytics Practice for Creative Computing and has more than 15 years of Business Analytics experience. Based in Providence, R.I., he has worked with many of New England’s most recognizable companies in Manufacturing, Retail, Healthcare and Higher Education. He is proficient in the entire IBM Business Analytics stack and is well versed in the entire Business Analytics project lifecycle.


Competitive Advantage: Business Analytics Provide Critical Tool

By Itzik Maoz, Director of Business Analytics Practice for Creative Computing, Inc.

Business analytics help organizations achieve many different strategic objectives — to compete in the marketplace, grow sales and retain customers, enforce integrity and security, improve business capacity, satisfy consumer expectations, learn more about the organization and/or implement necessary changes.

Whether we’re aware of it or not, we’re seeing business analytics at work on a regular basis in our daily lives. One of the most common examples is market basket analysis. Think of Amazon’s feature that tells you exactly what customers who bought a certain product were also likely to buy. This kind of data mining uses product and interest associations to predict groups of items that are more likely to be bought together.

Retailers use this method to stock shelves in situations where an item, say bread, is in close proximity to an item such as milk that is likely to be purchased together.

Another important type of analysis looks at “churn” rate — the number of customers who cut ties with a company in a given time period. Churn analysis helps companies distinguish the characteristics of likely-to-leave customers. They then can use that data to predict which customers are likely to churn in the future and offer incentives to those that generate more profits to keep their business.

In social media analytics, companies scan blogs, forums and comment sections to find out customers’ sentiments about their products. This data mining process will identify key words that might signify “good,” “bad” or “neutral” opinions. This is an emerging area but the technology for analyzing language is improving all the time.

Anyone with a credit card has probably come face to face with fraud detection analysis. If your bank has noticed red flag activity — say, a purchase at a store in a state you’ve never visited — it is using previously fraudulent patterns to raise the red flag. These processes have been improving and getting more efficient, so that now you may get a call within a very short time after a suspicious activity has occurred.

Personally, I’m most excited about healthcare data analysis applications. This is an area that can impact many lives, prevent illnesses, improve quality of life, shorten the treatment cycle when an effective drug is identified early in the process, etc.

This kind of analytics, of course, has much higher stakes than previous examples.
Think about the consequences of a false positive — a patient is diagnosed with a condition that he does not have — or a false negative — a patient with a condition that is not diagnosed. But with a careful and meticulous process, the risks can be mitigated.

If you are interested in learning more to understand what data science is all about, there are many books that can enlighten. For a technical understanding and implementation, IBM SPSS Modeler is a great way to get familiar with the subject without the need to be fluent in complex statistics. You can see a recommended LearnQuest course here.

Almost every organization can benefit from business analytics. While nobody can completely predict the future, companies that use analytics have been proven over time to be much more successful at what they do. The key is to identify which type will make strategic sense and to make the investment necessary to be a leader in your industry.

About the Author
Itzik Maoz is Director of Business Analytics Practice for Creative Computing and has more than 15 years of Business Analytics experience. Based in Providence, R.I., he has worked with many of New England’s most recognizable companies in Manufacturing, Retail, Healthcare and Higher Education. He is proficient in the entire IBM Business Analytics stack and is well versed in the entire Business Analytics project lifecycle.


IBM’s SPSS Modeler

By Itzik Maoz, Director of Business Analytics Practice for Creative Computing, Inc.

It wasn’t that long ago that companies looking to analyze data would hire a Ph.D. or otherwise experienced statistician to sit in a back room and write long lines of code with complex algorithms. That’s no longer the case, with IBM’s SPSS Modeler around to help business analysts to gain data-based insights.

SPSS Modeler is an extensive predictive analytics platform that allows business people who don’t necessarily have any statistics background to perform powerful analytic processes and integrate these processes with their decision management.

What IBM has done is simplify the user interface with an intuitive design. Nodes, which are graphic icons, perform tasks used for data preparation, modeling, exporting and importing.

SPSS allows the user to try out a variety of modeling approaches and compare the results. It can be extended beyond your typical numerical and categorical analysis to provide tools for text analytics to analyze social networks, for example.

In my LearnQuest classes, I show students what they need to know to get the most out of SPSS Modeler — a sense of the lifecycle and best practices of analytics, the ability to collect the right data, while cleaning any “noise” in order to reduce inaccuracies and anomalies. We examine a few models and talk about the uniqueness of each one and how we can leverage multiple models to enhance our predictive accuracy.

The Intro to Modeler class is focused on the process of data manipulation, but the more advanced courses examine specific techniques of analytics and their predictive applications.

Along the way I work with students to adapt the application to their individual needs, and by the end they come away empowered by sophisticated methods that traditionally required advanced degrees (with none of the student loans).

About the Author
Itzik Maoz is Director of Business Analytics Practice for Creative Computing and has more than 15 years of Business Analytics experience. Based in Providence, R.I., he has worked with many of New England’s most recognizable companies in Manufacturing, Retail, Healthcare and Higher Education. He is proficient in the entire IBM Business Analytics stack and is well versed in the entire Business Analytics project lifecycle.


On Board with Dashboarding: How to make the most of this dynamic visualization tool

By David Pacific. Education Services Practice Lead, Creative Computing

In business intelligence everything is trending toward the ability to gain quick insight — analyzing accessible data that allows you to make good decisions immediately. Enter the dashboard, a tool we are seeing more and more organizations utilize.

A dashboard can mean different things to different people, but typically when we define a dashboard in terms of business intelligence it is a group of graphical representations of any information that is important to an enterprise. A dashboard should tell a meaningful story with actionable insight. Its real strength is being able to display similar information in multiple formats — each provoking its own emotional response from the analyst.

There is a lot more to dashboarding than meets the eye. It is not simply a graph or chart, but a customizable visualization tool. This of course comes from a fundamental understanding of the toolset and its capabilities, as a dashboard consists of individual elements existing in pre-developed or managed reports. Having this understanding is a prerequisite for being able to develop effective dashboards, which is why I first guide students into Report Studio courses.

When we participate on dashboard projects with organizations, we usually start the conversation with data governance and standards. In order to put anything on the dashboard, all of the stakeholders need to be in agreement about what data should be presented. Getting that buy-in from the earliest stages of development will ensure that the dashboard will be effective for enterprise use. In a typical organization there are a multitude of data sources and a multitude of revenue sources, but each stream of data is going to carry its own implications, so you want to make sure the dashboard reflects the most relevant and comprehensive information.

What you are looking for is to develop some key performance indicators or metrics that can provide an immediate health check for the organization — a high-level snapshot that executives, sales or marketing can use. If something looks awry, they then have the capability to view it in more detail and at this point, either act upon it or pass the insight along to an actionable resource.

It is up to the developers to create an environment that provides the most insight. You want a dashboard that is as flexible and dynamic as possible. You want an intuitive interface that allows you to pass filters and change values to view different angles of the data at a moment’s notice. The best principle for design is to keep views of the data as simple as possible.

At the end of the day the dashboard is only going to be as good as the data it reflects. So get the buy-in, create some enterprise standards, and you’re on your way to dashboard success.

About the Author
As Creative Computing’s Education Services Practice Lead, David Pacific oversees all training engagements and participates in analysis and requirement gathering for all potential training opportunities. In this respect, he coordinates to identify training needs and provides a fit for scheduling and courseware. He also has a combination of onsite development skills, so when he is not overseeing or delivering trainings he is working on implementation for a multitude of Fortune 500 clients. This has helped him develop an excellent mix of skills sets between the classroom and real world development work, which has proven to be a valuable asset as a trainer.


Entering InfoSphere: A comprehensive platform with a wealth of tools for users

By Itzik Maoz . Director of Business Analytics Practice, Creative Computing

There is much excitement and interest in the new ways reporting and analytics can benefit organizations. But reporting and analytics cannot be perfected alone without quality, accurate and timely underlying data.

IBM InfoSphere is an enterprise scale platform that allows for a comprehensive solution around data warehousing, data integration, master data management, data governance and more.

There are many valuable tools in the InfoSphere suite.

DataStage is a highly sophisticated data extracting and transforming tool (ETL). Its parallel engine enables a developer to work with high volume jobs with fewer resources in faster time. Other benefits include the support of big data and Hadoop in rest and in motion.

As you can see in the image below, it has a user friendly interface which contributes to ease of use and maintenance.

QualityStage is another important tool that allows you to manage and mitigate the amount of time dealing with data issues. Data quality often turns to be the most consuming part of a project, and there are estimates that companies can save $7-$10 for every record, which amounts to significate savings.

Other tools in the InfoSphere suite include

Information Analyzer, provides advanced analysis and monitoring of your data, among other abilities.

Metadata Workbench helps link metadata from source systems with target systems such as Cognos BI with an end-to-end metadata path that can be used for impact analysis.
Organizations that use Cognos BI and InfoSphere can track their data from the report all the way to the source data. This type of tracking is valuable in creating a transparent environment, fostering trust and complying with many recent data tracking requirements.

Business Glossary is extremely valuable for organizations that want to maintain an enterprise glossary and vocabulary. It is connected to Metadata Workbench and allows data stewards to use a web-based interface to define the glossary and in turn have business users very easily understand the definitions.

With this wide range of data services that all work closely together, InfoSphere is a truly comprehensive platform — ideal for saving time, mitigating risk and moving data quickly and cleanly from source systems to a comprehensive analytics solution.

About the Author
Itzik Maoz is Director of Business Analytics Practice for Creative Computing and has more than 15 years of Business Analytics experience. Based in Providence, R.I., he has worked with many of New England’s most recognizable companies in Manufacturing, Retail, Healthcare and Higher Education. He is proficient in the entire IBM Business Analytics stack and is well versed in the entire Business Analytics project lifecycle.