OLTP vs OLAP Databases

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Ben Finkel
Nugget trainer since 2014
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Core Data Workloads and Data Analytics Concepts FAQs: Cost, Training, Value

What even is data analytics? What is a data workload?

Data analytics is the process of turning raw information into useful insights. Data analytics involves finding patterns in data and using them to assemble a bigger picture, one that helps make smarter decisions or clarify situations. Data workloads are tasks or processes that you run your data through in order to make it more useful. Workloads include tasks like organizing data, cleaning it, and figuring out what it's saying.

Is it worth it to learn about data workloads and data analytics?

Yes, it is absolutely worth it to learn the basics of data workloads and analytics. Ours has rapidly become a data-driven world, and skills related to extracting meaningful insights from large data stores are increasingly valuable. After this course, you'll understand how to efficiently handle large datasets and uncover patterns and trends from them, helping make smart and profitable decisions. IT and non-technical professionals alike are excellent candidates for data literacy.

Do I need a special background to get started in data analytics?

Previous training in data-related fields will always be helpful when studying data analytics, but this course is specially designed to be approachable to learners with diverse backgrounds. Starting with foundational concepts, beginners will have everything they need to excel. Familiarity with statistics and computer programming (like Python or R) will be helpful but isn't necessary, and experience with databases will also make the learning process easier.

Is this data analytics and data workloads training associated with any certifications?

No, this course isn't specifically designed as certification preparation material. It focuses on the foundations of data – the basics of navigating data workloads and implementing data analytics. While it doesn't aim to prepare you for certs like CompTIA's Data+, the broad familiarity with various approaches from this course will definitely make pursuing certifications like it easier. It serves as a solid foundation, enhancing your readiness for more specialized certification programs.

What are the different types of data analysis?

Generally speaking, there are four types of data analysis, which provide you with different sorts of insights: Descriptive, Diagnostic, Predictive and Prescriptive. Descriptive analysis summarizes and describes data. Diagnostic analysis deduces reasons behind certain outcomes. Predictive analysis tries to make future predictions. Prescriptive analysis recommends actions for optimal results. Taken together, these types of analysis reveal what happened, why it happened, what might happen, and what to do about it.
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