Tag Archives: intelligence

Trusted Data: Working Together and Communication Play a Big Part

Recently we found ourselves re-reading Educause’s annual Top 10 IT Issues, 2019 Edition. We commented on this publication when it came out, but we wanted to revisit in this post a few observations...

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Achieving Successful Reporting is Not a Technology Problem

While some organizations have been successful with a wide range of reporting tools, many others struggle with the same tools. We feel it is because organizational reporting or analytics problems are...

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Data Management Challenges Facing Institutional Researchers

Recently we attended the AIR Forum, the annual conference for institutional researchers. As a company, IData has a fair amount of direct experience with the practice of institutional research,...

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System Integration Project Best Practices - Part 2

In a previous post we covered 5 best practices in a system integration project.  Here we will cover 6 more best practices which are:

  1. Build a complete data mapping document
  2. Get approval on the...
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System Integration Project Best Practices - Part 1

In this post we cover 5 best practices for system integration projects and how data governance (data intelligence) can help.  In a following post we cover 6 additional best practices. Here are the 1st...

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What Does the Data Steward Do?

The data steward role is pivotal for the success of data governance and data intelligence. In a previous post we discussed the 3 data governance roles of steward, owner and custodian. The steward...

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Fit Data Governance into Your Higher Education Institution's Culture

In this blog post we’ll discuss the institution culture that will maximize the benefit of data governance at all levels. And that data governance needs to be a part of your higher education...

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Improve Data Quality - Do These Actions Part 2

A data quality program can be any size. Whether large or small, the key thing is to have a plan and to use processes that are predictable and repeatable. A haphazard or unpredictable approach will...

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80% Preparation, 20% Misinterpretation: Citizen Data Science in the Context of No Governance

This post is inspired by two pieces of terminology that have seemingly been everywhere this year, and one factoid that’s been circulating for years. One term is “self-service business intelligence,”...

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Improve Data Quality - Do These Actions Part 1

A data quality program can be any size. Whether large or small, the key thing is to have a plan and to use processes that are predictable and repeatable. A haphazard or unpredictable approach will...

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Back to Basics - What Goes Into a Business Glossary

Recently we discussed the differences between a business glossary and a data dictionary, and why you are likely to need both at your organization. In this post we want to delve more deeply into the...

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Data Governance Roles: Steward, Owner and Custodian

Data governance (also called data intelligence) consists of processes and tasks that staff perform within their organization. When these activities are executed well, all data users enjoy easier...

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Data Quality Responsibilities at All Levels

Building a culture that fosters data quality is the job of everyone in your organization (such as a higher education institution), from front line staff in various functional departments such as...

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Back to Basics - Data Dictionary vs. Business Glossary

Having accessible knowledge is an important part of data governance (or also called data intelligence) and we thought in this post (and in upcoming posts) we would go back to the basics. Topic this...

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Brainstorming About Data Quality

Data quality can be improved at any organization including higher education institutions. And it is a team effort with thoughts from many. To do this, we suggest getting individuals into a room...

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Internal Communication Regarding Data Quality

Internal communication is a key process in the success of a data quality program at an organization. To build trust in your data you want to be as transparent as possible regarding data quality. If...

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Trend for Shadow Analytics

In a previous post we shared some thoughts about shadow systems, and how they are symptomatic of poor data governance (data intelligence) practices as much as, if not more than, users seeking to...

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Top 10 IT Issues in 2019 in Higher Education are Data-related Dominated

Data dominates on EDUCAUSE’s annual list of the “top 10 IT issues” for higher education institutions as 5 of the issues are about data. Focus this year is about achieving trusted data and putting...

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Shadow Systems Explained

Everyone knows shadow systems are bad, and yet they still proliferate. Rather than enumerate once again why you should take pains to avoid them, we want to spend some time in this post exploring why...

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15 Thoughts on Improving Data Quality

Data quality is an important piece to data governance (data intelligence) and thus important for organizations including higher education institution. During our various webinars and blog posts we...

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Data Quality Content

Data quality is an important component of data governance and data intelligence at higher education institutions and organizations. Data quality includes people, processes and content. This blog post...

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Who Owns the Data

Who owns the data at organizations and higher education institutions? Information Technology (IT) Department or the specific functional department like Admissions, Human Resources, Institutional...

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Data Governance is Foremost About Helping, Not Controlling

This blog post discusses the perception of data governance (and data intelligence). It sounds difficult and controlling. Maybe it should be called data guidance instead. Data governance should help...

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Impacts and Sources of Data Quality Problems

Data quality is a key component of data governance (also called data intelligence). This post lists impacts of poor quality data and identifies sources of poor quality data. If you can’t get traction...

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Data Quality Issues

In an earlier post we covered components of a data quality programdata quality rules and data quality assessments. The last post in this Data Quality series recommends a process to address data...

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