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Database Technologies
Data+ Training and Certification Prep
CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making. CompTIA Data+ validates certified professionals have the skills required to facilitate data-driven business decisions.
Topics and skills covered in training include:
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Data concepts and environments
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Data mining and manipulation
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Data analysis
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Visualization and reporting
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Data governance, quality, and controls
This is a new CompTIA certification which was first introduced in February 2022. Jobs which use skills learned in this course include data, clinical, reporting, operations, and business intelligence analysts.
At the end of the course, you should be able to:
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Better analyze and interpret data by mining data more effectively, analyzing with rigor, and avoiding confounding results.
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Communicate insights through highlighting what’s important, producing reports that persuade, not confuse, and helping the team make better data-driven decisions.
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Demonstrate competency where you will be a more valuable team member. Proof of data literacy means you’re more employable and more upwardly mobile.
The Data+ certification exam is included with this course.
Required preparation:
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CompTIA recommends 18–24 months of experience in a report/business analyst job role
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Exposure to databases and analytical tools
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Basic understanding of statistics
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Data visualization experience
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Computer or laptop with a camera and microphone and robust Internet access
Please call The Continuing Education Registration Office at 808-845-9296 or email pcatt@hawaii.edu for assistance.
Introduction to Data Analysis
Introduction to Data Analysis sets a foundation for those interested in pursuing more advanced topics in data analysis.
Becoming a data analyst requires proficiency in several areas:
- Data wrangling
- Programming
- Statistical methods
- Machine learning
- Data visualization
There is truly a vast amount of open data available to anyone who knows where to find it, but data is often found in a form that does not lend itself to analysis.
Data wrangling is the use of tools and techniques to transform unstructured data into structured data from which descriptive, predictive, and prescriptive analytics can be derived. Business leaders depend on high-quality, real-time analytics to make informed business decisions. This "business intelligence" enables a company to differentiate itself from its competition, but high-quality, real-time analytics is the end game. One has to walk before they can run. Data analysts often point out that roughly 70% of their work involves data wrangling.
This course sets you on a successful path in data analysis by building a solid foundation. A course will follow that introduces learners to machine learning via Microsoft Azure Machine Learning Studio.
Recommended preparation: Algebra and basic statistics. No programming experience is required - the necessary R programming will be learned in the context of working with data sets.