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Business Intelligence Software: 6 Steps to Successful Installations

Dec 20, 2016 10:16:45 AM   Matthew Caton & David Crolene

Topics: Business Intelligence, Program Management, Blog

Business Intelligence Software

By:  Matthew Caton and David Crolene

Business Intelligence software comes in all shapes and sizes.  Some tools promise industry specific solutions with a relatively narrow set of functionality, while others provide a greater breadth of capabilities that can be tailored to the needs of more sophisticated BI organizations.  It is this latter class of business intelligence software – the enterprise class – that is not always easy to install and configure.  Tools like IBM Cognos, MicroStrategy, SAP Business Objects, Tableau and Oracle Business Intelligence Enterprise Edition (OBIEE) are representative of this class and consistently appear in the upper right-hand corner of Gartner’s Magic Quadrant as best in breed.

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Agile Business Intelligence – Increasing the Velocity of Reporting and Analytics

Dec 20, 2016 10:15:44 AM   David Crolene & Donnie Evans

Topics: Collaboration, Agile, Program Management, Data Virtualization, Blog

Agile Business Intelligence: Increasing the Velocity of Reporting and Analytics

By:  David Crolene and Donnie Evans

One of the biggest complaints we hear from business users is that it takes too long to develop reporting and analytics when working with IT. Some BI programs have turnaround times ranging from weeks and even months from the time a business unit requests a report. By that time, the business has often found a different source for the information, or the issue or no longer relevant.

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How Partnerships Between IT and the Business Breed Success

Dec 13, 2016 2:25:00 PM   Nancy Couture

Topics: Program Management, Blog

The stakes are high in the world of analytics and reporting.  According to Gartner: through 2016, only 10 percent of self-service business intelligence initiatives will be sufficiently well governed to prevent inconsistencies that adversely affect the business.  Without appropriate processes and governance, self-service capabilities can introduce multiple versions of the truth, increase errors in reporting, and leave companies exposed to inconsistent information.  So how can an organization find the right balance between the traditional IT development process and more innovative data discovery in the business?

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How to Integrate Business Data with Business/IT Partnerships

Nov 21, 2016 9:43:35 AM   Nancy Couture

Topics: Data Governance, Data Integration, Program Management, Blog

Continuing with the theme of business / IT partnerships, another example I’ve been involved in is integrating business data into an IT managed environment – in this case, an enterprise data warehouse. 

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How Business - IT Partnerships Develop Operational Analytics

Nov 21, 2016 9:39:56 AM   Nancy Couture

Topics: Data Quality, Data Integration, Program Management, Blog

A great example of business and IT working together to innovate is in the development of operational analytics. As data volumes and frequency of data continue to increase, organizations have realized that it’s not enough to analyze their data – they must take action on it. 

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5 Tips for Leading Agile Data Management Development Teams

Aug 9, 2016 3:37:32 PM   Nancy Couture

Topics: Agile, Program Management, Blog

One of the principles behind the Agile Manifesto states:

The best architectures, requirements and designs emerge from self-organizing teams.

This is a key success factor in agile data management, whether the team is developing a traditional data warehouse or any other type of enterprise data management solution. 

Self-managing teams can be very effective due to the following factors:

  • Better, faster communication.
  • More trust between client and product team.
  • Less conflict.
  • Increased motivation.
  • Informed decision-making.

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Don’t Treat Data Like An Asset

Jul 7, 2016 7:00:00 AM   Datasource

Topics: Data Governance, Program Management, Blog

It has been ringing in our ears for years – incessant voices of the data pundits, professionals and practitioners encouraging us to treat data as an asset. With the recent big hype around big data, the voices only grow louder and well, bigger. As someone with a peculiar enthusiasm for business data who has spent nearly 30 years helping organizations optimize the value of their information, I have been one of those voices. We think this asset-oriented thinking will encourage organizations to treat data better, wring more value from it and place a financial value on it. We have been mistaken and it’s time to change our tune. We do data a disservice when we encourage others to treat it like an asset – it is so very much more than that.

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Assess Before You Leap: The Value of Assessments

Jun 30, 2016 5:32:00 AM   Nancy Couture

Topics: Program Management, Blog, Project Management

As organizations strive to continue responding to market changes and opportunities, there is an increasing need for operational and strategic information to better support the business. Before committing to or starting work on a large Business Intelligence (BI) initiative, which is typically a significant investment, organizations are increasingly recognizing the advantages of conducting a program assessment.

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Enriching the Value of Your Data Assets

Jun 17, 2016 7:00:00 AM   Datasource

Topics: Data Governance, Program Management, Blog

It amazes me -- but probably shouldn't -- how many organizations accept the data they depend on every day at face value, and yet do not understand how it comes together. They seek to be "data-driven" yet they are not willing to invest in understanding how data drives the organization, how it could be dramatically improved, and then they wonder why they are missing that performance edge that smart executives seek.

Enterprise performance depends on having certainty about the derivation of the entire data chain. If you drive a car, you don't worry about how the car works, but you do develop some degree of trust in the quality of engineering that put the car together. Auto engineering has over time much smarter about the entire process, from design through delivery, and engineers have built quailty in to their products in part through ensuring all components work well together.

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Customer-Centric Data Driving Growth for Credit Unions

Jun 2, 2016 9:29:41 AM   Datasource

Topics: Program Management, Data Warehousing, Blog

Why you need a modernized data warehouse and BI environment and what it looks like

Most credit unions grew up in an era where custom-built data environments reigned supreme. Excel, SQL, and Microsoft Access were the workhorses of the data warehouse. Everything from member data to transaction data were tracked across multiple applications and spreadsheets. What started out as a solution for data to a handful of users was expanded and layered upon overtime, becoming unwieldy and inefficient  

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