Qlik Case Studies Rounding the Bases: How Qlik Helped Us Bring Data Literacy Home

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	Rounding the Bases: How Qlik Helped Us Bring Data Literacy Home Qlik

Rounding the Bases: How Qlik Helped Us Bring Data Literacy Home

Qlik

Technology Category	Analytics & Modeling - Predictive Analytics Analytics & Modeling - Real Time Analytics
Applicable Industries	Education Healthcare & Hospitals
Applicable Functions	Human Resources Quality Assurance
Use Cases	Predictive Maintenance Real-Time Location System (RTLS)
Services	Data Science Services System Integration
Challenge	The article discusses the challenges faced by organizations in their journey towards data maturity. The first challenge is related to data quality. Organizations often have data quality issues, which become more apparent as they try to utilize the data. Issues can range from misspellings, inconsistent data entry methods, to software compatibility issues. Before any progress towards data-based decisions can be made, the data itself must be trustworthy. This requires creating mechanisms to ensure data quality. The second challenge is related to data literacy. Having great data is just part of the equation. Organizations must also have a genuine curiosity and the ability to ask the right questions. Most organizations are very familiar with asking, “what happened?” but the real power in analyzing data comes from more advanced questions. The final stage of intuitive growth involves reaching a level where insights about data trends lead to an ability to influence outcomes. Read More
About Customer	The article does not provide a specific customer description. However, it mentions the author's experience with data journeys at several organizations, including his current role as the manager of education at 2Foqus Data & Analytics. The author is a Qlik Luminary, indicating a high level of expertise in using Qlik for data analysis. The author also shares his experience working on a healthcare service project titled Call To Balloon, which aimed to shorten the time between an emergency call and the performance of treatment. Another example provided is from the author's experience at UWV, where he was charged with writing the plan to centralize the QlikView Competence Center. Read More
Solution	The solution to the challenges faced by organizations in their journey towards data maturity involves several steps. The first step is to ensure data quality. This can be achieved by creating mechanisms to ensure data quality. For example, Qlik Sense users may find it useful to add a data quality report to the environment. The early steps in the journey must include creating some kind of data governance solution. The second step is to develop data literacy within the organization. This involves training people to analyze and argue with data. Platforms like Qlik Sense can make data reading and manipulation second nature, but people must be trained to analyze and argue. The final step is to develop a predictive analysis. This is where the true value for the company begins to emerge. Analyzing real-time product sales and production data can help a company avoid bare shelves. Traffic patterns and customer addresses can help you make an optimum choice for a new location. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Analytics & Modeling - Real Time Analytics

Applicable Industries

Education

Healthcare & Hospitals

Applicable Functions

Human Resources

Quality Assurance

Use Cases

Predictive Maintenance

Real-Time Location System (RTLS)

Services

Data Science Services

System Integration

Challenge

The article discusses the challenges faced by organizations in their journey towards data maturity. The first challenge is related to data quality. Organizations often have data quality issues, which become more apparent as they try to utilize the data. Issues can range from misspellings, inconsistent data entry methods, to software compatibility issues. Before any progress towards data-based decisions can be made, the data itself must be trustworthy. This requires creating mechanisms to ensure data quality. The second challenge is related to data literacy. Having great data is just part of the equation. Organizations must also have a genuine curiosity and the ability to ask the right questions. Most organizations are very familiar with asking, “what happened?” but the real power in analyzing data comes from more advanced questions. The final stage of intuitive growth involves reaching a level where insights about data trends lead to an ability to influence outcomes.

About Customer

The article does not provide a specific customer description. However, it mentions the author's experience with data journeys at several organizations, including his current role as the manager of education at 2Foqus Data & Analytics. The author is a Qlik Luminary, indicating a high level of expertise in using Qlik for data analysis. The author also shares his experience working on a healthcare service project titled Call To Balloon, which aimed to shorten the time between an emergency call and the performance of treatment. Another example provided is from the author's experience at UWV, where he was charged with writing the plan to centralize the QlikView Competence Center.

Solution

The solution to the challenges faced by organizations in their journey towards data maturity involves several steps. The first step is to ensure data quality. This can be achieved by creating mechanisms to ensure data quality. For example, Qlik Sense users may find it useful to add a data quality report to the environment. The early steps in the journey must include creating some kind of data governance solution. The second step is to develop data literacy within the organization. This involves training people to analyze and argue with data. Platforms like Qlik Sense can make data reading and manipulation second nature, but people must be trained to analyze and argue. The final step is to develop a predictive analysis. This is where the true value for the company begins to emerge. Analyzing real-time product sales and production data can help a company avoid bare shelves. Traffic patterns and customer addresses can help you make an optimum choice for a new location.

Impact #1	Improved data quality through the implementation of data governance solutions.
Impact #2	Increased data literacy within the organization through training and the use of platforms like Qlik Sense.
Impact #3	Developed predictive analysis capabilities, enabling the company to make more informed decisions.

Impact #1

Improved data quality through the implementation of data governance solutions.

Impact #2

Increased data literacy within the organization through training and the use of platforms like Qlik Sense.

Impact #3

Developed predictive analysis capabilities, enabling the company to make more informed decisions.

Benefit #1	With the Call To Balloon and Call To Needle projects, more than 20 minutes were shaved off the patient wait time.
Benefit #2	At UWV, the number of QlikView users increased from fewer than 100 to more than 3,000 in five years.

Benefit #1

With the Call To Balloon and Call To Needle projects, more than 20 minutes were shaved off the patient wait time.

Benefit #2

At UWV, the number of QlikView users increased from fewer than 100 to more than 3,000 in five years.

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Overview

Rounding the Bases: How Qlik Helped Us Bring Data Literacy Home

Operational Impact

Quantitative Benefit