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SunGard (SNUG) 2016 National User Conference

It’s here – SunGard 2016 National User Conference

SunGard 2016 National User GroupLooking forward to seeing everyone at SNUG 2016 National Users’ Group Conference coming up next week in Ft. Worth. Hopefully you have selected your vendor sessions, but if not, sign up for one of our Cognos sessions:

Tuesday, October 11th, 2:00pm – 2:30pm: Cognos Training, Mentoring, and Dashboard Examples

In this session, we will discuss the training and mentoring options available from Capitalize and SunGard to ensure you’re fully utilizing the capabilities of IBM Cognos. We will also highlight some of the district solutions we’ve worked on recently that have helped districts Liberate Their Data! Add session to your schedule.

Wednesday, October 12th, 2:30pm – 3:00pm: Connecting Cognos to Other Data Sources.

In this session, we will show you how to pull new data sources into your Cognos environment. Cognos can pull from any system in your district, helping you to Liberate Your Data! Add session to your schedule.

Predictive Analytics – Worth the Investment?

The answer is YES! I have written a few blogs about predictive analytics, but wanted to take a small step back and define predictive analytics. There are various thoughts, ideas, perceptions etc. and a lot of talk about predictive analytics being the next wave in big data analytics. But what is it exactly? Remember the movie Minority Report? Well, we aren’t quite there – where we are predicting whether anyone will actually commit a crime – but, the concept of using big data to predict potential scenarios and bring new insights for your organization is here.

Predictive analytics allows you to add what/if scenarios alongside your historical data. It brings together advanced analytics capabilities spanning ad-hoc statistical analysis, predictive modeling, data mining, text analytics, entity analytics, optimization, real-time scoring, machine learning and more. It allows you to move forward from static reports to a more intelligent decision-making process. Basically, it helps guide you with answers to What happened?  Why?  What next? 

Predictive technology is here. Recently, Forrester Research looked at the major big data predictive analytics solutions and identified the top three (see page 11). At the highest point for leadership and market presence is IBM—which makes sense given that IBM has invested heavily in this space.

IBM and Predictive Analytics

Many people are aware of IBM Watson, the computer that beat human competitors Jeopardy! and talked with Bob Dylan about a possible collaboration. Watson is pretty cool, but there is another key component to IBM’s predictive solutions – IBM SPSS.

Some organizations struggle to get the maximum business value out of their data. IBM saw an easier way through SPSS. There are two primary modules that you work with: SPSS Modeler, which helps you create predictive models for your business processes, and SPSS Statistics, which provides advanced statistical analysis of your data for deep insights into your business challenges.

These two modules can be deployed in multiple configurations based on your unique requirements and the needs of various business units. The power of IBM SPSS predictive analytics solutions provide benefits across the entire enterprise. It puts capabilities into the hands of business users, data scientists, and developers.

Some examples of where predictive analytics is having an impact in various industries as well as areas within organizations are:

Customer Analytics – Understand who your most lucrative customers are, the best ways to attract them, and how to maximize their lifetime value through up-selling and cross-selling strategies. IBM SPSS has a social media analytics tool to help you tap into social media data to learn more about your customers and build a deeper connection.

Operational Analytics – Gain better visibility into your processes, people, and assets. Optimize your operations to maximize profitability and productivity. Inventory management improves through predictive analytics when you can bring in more data from sales forecasts, cyclical trends, market conditions, social content, and more.

HR Analytics – Use the data you currently have on employees to find, attract, and retain the best people. Based on your business information, you can not only help put your team in the best position to be successful, but you can also forecast future staffing requirements. HR recruiters can be more proactive instead of simply reacting to work orders and focusing on individual transactions.

Asset Analytics – Maximize the lifetime value of your critical assets. Use predictive analytics to optimize uptime by avoiding unexpected errors and proactively maintaining equipment. You can gain greater insight into the use of your assets so that you can make more informed purchasing decisions in the future.

Fraud and Threat Analytics – Secure your data, applications, and money using predictive data analytics, which is increasingly becoming more important in these areas. Every threat cannot be accounted for. It requires constant and consistent monitoring while assessing activities for suspicious behavior. And if there is an incident, how quickly you react can greatly affect your business. If you are the victim of a major fraud, that usually becomes apparent pretty quickly. However, smaller hits could take months to uncover. Very often, data breaches are not detected for over 6 months. Unlike losing money, when someone steals copies of your data, those files do not disappear.

K-12 Organizations –  School districts, colleges and universities are making the most out of their decisions by analyzing trends and predicting future outcomes centering around student retention, student enrollment, student performance/success and institutional research. 

Predictive Analytics Is Here

Implementing a predictive analytics solution can be the single most important investment you make in 2016. A successful implementation can alter the competitive landscape of your industry. You want to make sure that you choose a platform based on best-of-breed capabilities. In order to help, you can take a look at this study from Forrester Research, in which they evaluate 13 solutions and name three leaders in predictive analytics solutions.

Optimize the future with better decisions today. Let’s work together and put a predictive analytics plan together for your organization. Give us a shout today!

The 2 Hottest Buzz Words in Technology Today

Two of the hottest buzzwords in technology today: Internet of Things (IoT) and big data analytics.

Let’s start by defining what these technologies are. Internet of Things (IoT) is the amount of items that are connected to the Internet – which is about to skyrocket. IoT technologies can be found in all kinds of different industries from agriculture all the way to energy and transportation. In many cases, these devices are tiny, inexpensive sensors that report information back to large data collectors. The data can be for maintenance reasons or to improve performance.

Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include different types such as structured/unstructured and streaming/batch, and different sizes from terabytes to zettabytes. Big data is a term applied to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage, and process the data with low-latency. And it has one or more of the following characteristics – high volume, high velocity, or high variety. Big data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media – much of it generated in real time and in a very large scale.

Gartner predicts that there will be 6.4 billion devices connected to the Internet by the end of 2016. They will be joined by 5.5 million new devices every day. These sensors could be items in your home, including your coffee maker, however the larger application of IoT is in the corporate world.

Take oil and gas organizations for example, there is data generated by all of the devices, control systems, sensors, SCADA, networks, applications and end users connected by industrial networks. With advances in sensors, the amount of data points has escalated so much that it now requires a new way to analyze that data. That is driving the advancement in big data analytics. Now, sensors can make it into many other applications. Big data analytics can be used to improve and streamline transportation, refinement, and distribution of oil and gas. Data gathered from a drill-bit or a reservoir might provide information that can save millions in production costs if it can be analyzed and combined with other data sources.

These insights are invaluable to this industry – especially during times of reduced oil prices and increases in competition. Now is the time for organizations across all industries to start preparing to ensure you are ready to take advantage of the tangible benefits that you can gain by leveraging machine data and the IoT.

Data Quality and Governance

Getting the most from data and making accurate decisions starts with quality data. All of the analytics in the world won’t matter if the data at the core is inaccurate.

The data also needs to be opened up to everyone in the organization who could benefit from it. Data traditionally resides in silos by department. IBM self-service solutions enable access to relevant data without having to rely on a technical expert or jump between numerous applications. Users can find answers quickly—on their own and take full advantage of analytics. You may learn that production and distribution are asking the same questions. Their data, when combined, could lead to millions in cost savings.

Predictive Analytics

The cost benefits created through big data analytics extends to just about any industry. If an asset such as a crane could predict when it was going to have a failure, maintenance could be scheduled in advance at a convenient time. This saves on maintenance costs, as well as improves productivity.

For a big data analytics project to benefit an organization, it needs to be data-driven, be actionable, and generate a monetary impact.

To learn how big data analytics and the expanded use of IoT can be used to improve your business and gain a competitive edge – let’s talk! Schedule a meeting with one of our data analytics experts today.


Top 5 Must-Go-To IBM Cognos Events

This time of year there are a lot of things going on – school is back in session, football is in full swing (yeah!) as well as a host of wonderful, fun community festivals like Octoberfest! The same is true in the world of Cognos – lots of things going on and some really great events coming up. Below are 5 of the “must-go-to” IBM Cognos events.

Capitalize Analytics SNUG2016SunGard National User Group (SNUG) Conference – Ft. Worth, TX, Oct. 10th-13th, 2016

We are excited to be a sponsor of this great event and it’s right here in our own backyard this year! SNUG is an educational, informative and professional development conference filled with sessions from respected SunGard K-12 subject matter experts, covering a wide variety of education-oriented topics, future technological trends and directions and much more!

Capitalize Analytics Splunk Dallas LiveSplunkLive! – Dallas, TX, October 13th, 2016

Please join us October 13th for SplunkLive! Dallas – and learn how more than 10,000 enterprises, government agencies, universities and service providers in over 100 countries use Splunk software to deepen business and customer understanding, mitigate cybersecurity risk, prevent fraud, improve service performance and reduce cost. You’ll hear from industry experts, customers and technologists on how they’re turning machine data into actionable insights.

Capitalize Analytics IBM SPSSIBM SPSS Predictive Analytics Data Mining Workshop – Houston, TX, October 20th, 2016

Join IBM SPSS experts in Houston on Thursday., Oct. 20th for a hands-on workshop. This event will focus on key areas geared toward helping organizations make the most out of their decisions by analyzing trends and predicting future outcomes. IBM experts will help you better understand the distinctive value of the easy-to-use, rapid prototyping, predictive modeling capabilities of Modeler software.

IBM Insight 2016 ConferenceIBM Insight 2016 – Las Vegas, NV, Oct. 24th-27th, 2016

IBM Insight 2016 is coming up @ Mandalay Bay, Las Vegas. See how to apply the latest advances in data science and analytics to gain unexpected insights that are hidden in your data. You won’t want to miss the Insight Expo either. This is the place where attendees can meet IBM Business Partners, preview new technology, and can check out hundreds of innovative products. Mark your calendar to attend IBM Insight 2016!

Capitalize Analytics Cognos WebinarLive Webinar: Cognos Reporting Tools – Wed, Nov. 16th, 2016 10:00am – 10:30am CDT

Discover how to create compelling interactive reports. A picture is worth a thousand words – it really is true. That’s why people want engaging visuals in their reports; it helps them make sense of all that data. If you’re responsible for delivering those reports, this webinar will show you how Cognos provides the fundamentals you need to create the interactive reports people want.

Capitalize Analytics Becomes a Splunk Reseller

Exciting news!

Capitalize Analytics is now a premier reseller of Splunk Operational Intelligence solutions! Capitalize Analytics will distribute Splunk Enterpise, Splunk Cloud, Splunk IT Service Intelligence and Splunk App for Enterprise Security. So now you’re asking, “What the heck is Splunk?”

I’m sure your organization is like every organization in that you are producing HUGE amounts of data, but a lot of the data that is produced is unstructured and most of it tends to be viewed as unusable or kept in a silo where its value is squashed!

You need the answers that this data provides and there are no limits to the value that you can derive from your data…whether it’s to improve your organization’s security posture, to automate compliance, enhance IT operations, optimize application delivery, or drive better insights through business analytics.

Now, imagine there is a tool that can monitor and analyze everything from customer clickstreams and transactions to network activity and call records. AND, this tool allows you to EASILY access every log file in a searchable way turning that unstructured data into something you can query, like a database. THAT’S SPLUNK!

  • Splunk Enterprise collects, indexes, monitors, analyzes and visualizes machine data being generated by websites, applications, servers, networks, sensors, mobile devices and more. Customers gain real-time visibility and insights from Splunk Enterprise in multiple use cases including IT operations, application management, security, compliance, digital intelligence and business analytics.
  • Splunk Cloud delivers Splunk Enterprise in the cloud, providing organizations visibility and operational insights into their machine-generated big data in the cloud, as well as the ability to correlate this data across their cloud and on-premises environments.
  • Splunk IT Service Intelligence is a next-generation monitoring and analytics solution that provides new levels of visibility into the health and key performance indicators of IT services.
  • Splunk App for Enterprise Security provides monitoring, alerting and analytics to identify and address known and unknown threats in real time with out-of-the-box content.

Eric Soden, Managing Partner at Capitalize Analytics stated, “Capitalize Analytics is looking forward to providing our clients and organizations with this exciting tool! This partnership opens the door for Splunk Enterpise, Splunk Cloud and Splunk IT Service Intelligence solutions to help more organizations leverage machine data for deeper IT and business insights.”

We invite you to take advantage of a complimentary Splunk demo and learn how Splunk and Capitalize Analytics can help your organization gain deeper IT and business insights. Give us a shout today!

The Impact of Analytics Throughout Your Organization

The other day I was digging around in the extra closet trying to find some shoes that my daughter was needing – IMMEDIATELY. Of course I couldn’t find anything in there, I had to pull stuff out, move things around, etc. until voila, I found the shoes – 2 hours later! Why these shoes were even in the extra closet and not her own closet, I have no idea. My point is that different objects reside in different environments but they still need to be accessed easily.

Sometimes this same type of scenario happens at work, when you are looking for important data that you need. You need to get to information (data) because someone is asking you for it but you just can’t get your fingers on it. There is so much data collected by everyone that it can be hard to put this data to good use, gain insight or analyze what future scenarios could possibly happen.

As we discussed in a previous blog post, a recent survey showed that 87% of businesses expect big data analytics to transform the competitive landscape in their industry over the next three years. But getting to that data, which could be in different environments (closets, if you will) can be a somewhat frustrating task. We can help get to the data so you can use all this data to your advantage.

Analyzing data to make faster, more informed decisions is incredibly powerful. Predictive analytics takes that power to another level. It goes beyond simply reporting on the past. It takes into account many factors, including business growth, cycles, and any other data points that are relevant to giving you a look into the future.

Let’s take a look at how the impact of predictive analytics will be felt throughout the organization.

Marketing Managers: Marketing is obviously excited about new technology. Consumers are generating a wealth of data from mobile devices, computers, communications, and transactions. They are also producing data in social networking feeds. For this data to be valuable, you need systems to respond to it in real time. That takes more than just reports. A recent IBM study found that 90% of marketers feel that personalizing the customer experience is critical to their success. That same study says that 4 out of 5 consumers believe brands don’t know them as individuals.

Predictive analytics can be used to provide additional products that may interest customers based on all of that information. It can use what/if scenarios to determine the right prospects to target. It can calculate the types of customers that have the highest lifetime value and the best ways to extract that value.

Sales Managers: Sales shares a lot with marketing. They go hand-in-hand with generating revenue and profit. Predictive analytics can help the sales team know when to approach existing customers with additional products or services. It can also help them understand new products or services that they should be offering.

Purchasing Managers: They are looking for new ways to analyze price points and contractual options that are being offered by their top providers and combine that with the state of the market. The purchasing manager’s goal is to demonstrate to executives that they are able to comb the market for the best possible deals. They will then use that insight to negotiate favorable terms with existing and new suppliers.

IT Managers: Much like purchasing managers, IT has to evaluate a wide spectrum of options and vendors. They have become skeptical of promises made by those vendors. IT managers want to validate the functionality of a platform and ensure there are no hidden costs. They regularly use white papers, social media, case studies, and peer reviews to make decisions.

Human Resources: HR has lagged behind other departments in their use of data analytics. According to Deloitte, only 14% of HR departments are using analytics. However, this may soon change because HR is drowning in transactional issues. The shift will be for HR to provide advice to management in operations, sales, and finance on hiring decisions and reducing turnover. They can analyze the characteristics of successful employees in a particular role to help hire prospects with similar traits. This can dramatically reduce training costs.

Operations Manager: Among the many needs of Operations, one major need is to forecast inventory. To do this effectively they need to take into account many variables including business cycles, growth, and combine it with outside data such as market performance, related industries, and possibly even weather trends depending on the industry. Many industries today try to predict usage to set pricing (think about airlines or hotels). Automated predictive analytics can provide them with more tools to maximize their profits.

Moving into the Future
Predictive analytics can benefit all areas of the organization. This extends from the office of the CFO to business analysts. Every employee who has to analyze data to make recommendations or decisions can be more productive with a predictive analytics solution.

These are just some of the use cases today for predictive analytics. And we can comfortably predict that there will be more uses that we have not even considered yet. How are you going to benefit from predictive analytics?

Watch this video on analyzing your past & present to shape your future to see how companies are using IBM Analytics – then, give us a shout and we can help you get started!

Assembling the Data Puzzle with Analytics

Feeling a bit overwhelmed by all the data that your organization is collecting? Sales has customer histories in their CRM, Finance has product revenue information in their accounting package, Operations keeps inventory data in their inventory management system, Human Resources has employee information in their HR management tool and Marketing has consumers that are generating a wealth of data from mobile devices, computers, communications, and transactions. However, Forrester Research estimates that organizations are only using 12% of their data for analysis and insights.

Why is it that we are only using a fraction of the data that is available to us? Part of the problem is that much of the data generated and captured is being stored in silos. And most of the systems that these different departments use, simply don’t talk to each other. If we had a complete picture from all the data we collect, organizations can increase efficiency, reduce waste, and improve sales.

We all know that the amount of data available to your business is only going to increase. Companies that are able to gain insights from that data are the ones that are going to succeed. A recent survey showed that 87% of enterprises feel that big data analytics will change the competitive landscape of their industries within the next three years.

Assembling the Data Puzzle – Hypothetical company “A”
To understand how data analytics benefits an organization, sometimes it is easier to picture it in use. Imagine a hypothetical company A. Company A manufactures three lines of widgets and sells them globally. They have also implemented an analytics tool that integrates with the systems and data in each department to give a complete picture of their organization.

Lynn is an Executive Manager at company A. She has noticed that one line of widget’s European revenue has increased when some new sales tactics were implemented. So she does some what-if analyses and determines that similar results could happen in the US.

She assembles a team that includes US sales leadership, operations, marketing, and finance. A note is sent over to Mike in sales. He looks at the tactic and reviews his team to see if he has the resources available. He decides he does, but not without significant help from marketing and customer service. Mike contacts Sue, the marketing lead on the project to see how they can support the initiative.

Meanwhile, John in finance is monitoring the numbers and forecasting the impact on all departments based on the sales forecast. Dan in operations is monitoring the initiative through a custom dashboard. He has filtered it based on his criteria, including inventory management and demand forecasts. Here, he can monitor decisions in purchasing, distribution, and logistics to ensure they can maintain the inventory levels they need.

The project is gaining traction and the company is seeing results. Sue in marketing notices that there could be a similar opportunity in some of their Asian markets based on some of the social information she is tracking. She contacts Lynn on the executive team with her ideas. Lynn does some further analysis and feels it is worth a test project—and the cycle starts again.

There is so much information available to organizations today. It will be the ones who can best analyze that data to make educated decisions who will have the competitive advantage. They will be able to respond to new business opportunities, maximize profits, and improve efficiencies.

Take Bugaboo International, a Dutch design company that makes pushchairs for infants and toddlers. They wanted to reduce the time necessary to generate accurate financial and sales forecasts and broaden the scope of reporting to meet the needs of the business better. The company also wanted to reduce its management load.

“We have one easy to manage planning model containing all of the data we need to generate our financial and sales forecasts and also a wide range of other reports for the business.
– Krzysztof Pabich, business intelligence specialist at Bugaboo

If you are ready to learn more about how companies are benefiting from analytics, take the next step and download this case study, Bugaboo: faster and more accurate forecasting.

Using an “If Then Else” Statement In a Filter

Another great Cognos Tech Tip from one of our expert consultants. Thanks Trevor for providing this one!

You can use if then else statements in a filter as long as you have a static answer (or set of answers) to complete the filter logic, rather than using column names like you would in a calculation.

Cognos Prompt ReportThe filter in the screenshot is for a report that will show students with less than 80 minutes scheduled each day. The prompt will default to 80 unless they enter their own value in the text box prompt on the page. This is also pretty helpful because they don’t need a prompt page, they run the report at 80 and then have the option to change it if they need to. Without the if then else, they would have to answer a prompt to complete the filter logic before running the report.

Cognos If Then ElseThe filter was set to optional, with a default value of 80 to show in the box.

Is Your Organization Ready for Self Service Analytics?

The Trend Towards Self-Service in Business Intelligence – Are You Ready?

According to Gartner, a major shift is occurring in the balance of power for companies. Business users and other departments outside of IT need to have access to the data they need for Business intelligence (BI) and analytics and quickly find answers on their own. For the average user, making use of  data can be daunting though. After all, the perception is that it would take an expert to access and make use of their unstructured data.

The technologies that make it easy to identify, explore, verify, analyze, report, predict, and share information exist today.

As they gain access to critical data, business users will have to be prepared for the task of preparing data for analysis. Rita Sallam, Research Vice President at Gartner, explains that “Data preparation is one of the most difficult and time-consuming challenges facing business users of BI and data discovery tools, as well as advanced analytics platforms.”

In response to this shift, companies will have to enlist tools that empower workers to prepare and analyze data for insights without mastering algorithms and data science. Accordingly, Gartner predicts that by 2017, most organizations will give their users and analysts access to self-service tools that automatically prepare data for analysis.

Preparing for Self-Service Analytics

Currently, most companies are not prepared for the shift from IT to the everyday user. Gartner’s research shows that 70% of users in organizations lack a statistical background and, in spite of this, do not use BI tools that could help them process data. Without access to BI tools, employees are forced to juggle spreadsheets to make sense of all the information that’s coming in from multiple sources.

Another problem arises in that users lack confidence in the quality of the data they need to make decisions. A vast amount of data is streaming into companies, and much of it is unstructured. Information comes in from legacy databases, ERP systems, CRM applications, and real-time operations, and customer transactions on your website and mobile applications.


As employees from different departments begin using analytics, they need to be able to judge the quality of the source data they use to make decisions. In its list of the top 5 BI problems, Information Management cites ignorance about data quality as a contributing factor to lack of BI readiness. Without the correct information, your business will miss out on insights that could help you collaborate, streamline business processes, and improve customer service.

Business Intelligence = Empowerment

The tools that most users need to harness the power of BI and analytics are out there. You don’t need to be an expert in BI or data science to use IBM Cognos Analytics. This unified solution eliminates the need for data prep. You can feel confident in the accuracy of the source data because data governance is built right in. With IBM Cognos, data is curated so you eliminate risk and can trust the validity of decisions you base on your information.


IBM Cognos Analytics bridges the gap between governance and self-service with:

  • A user-friendly interface
  • Natural language intelligence to respond to queries in your own keywords
  • A personalized dashboard to replace spreadsheets
  • Graphic reports to easily identify patterns and trends

As companies move BI processes from IT to the general workforce, be prepared by arming your team and organization with the latest self-service BI analytics tools.

Contact us today and we can provide recommendations tailored to help you on your journey to better self-service analytics and better business decisions.


When doing a union query, is it better to use UNION ALL versus UNION? The UNION will try and eliminate duplicate rows between the two queries and essentially does a select distinct on the entire query. Most of the time when doing a union, users build the queries so that each query returns unique results and therefore they don’t need UNION. So, if you have a slow union query, try changing to UNION ALL. Bottom line: UNION ALL does not remove duplicates, therefore it is faster than UNION.

Thanks to our two expert consultants Brian and Emily for providing this great SQL tech tip!