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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

On the flip side, if you enjoy diving deep into the technical side of things, with the right mix of skills for business intelligence you can work a host of incredibly interesting problems that will keep you in flow for hours on end. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

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Take Your SQL Skills To The Next Level With These Popular SQL Books

datapine

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

The Data Scientist profession today is often considered to be one of the most promising and lucrative. The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. Previously, such problems were dealt with by specialists in mathematics and statistics.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Let’s consider the differences between the two, and why they’re both important to the success of data-driven organizations. Digging into quantitative data. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?” The challenge comes when the data becomes huge and fast-changing.

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The Top Three Entangled Trends in Data Architectures: Data Mesh, Data Fabric, and Hybrid Architectures

Cloudera

The data product is not just the data itself, but a bunch of metadata that surrounds it — the simple stuff like schema is a given. Note that the actual technologies used to generate, store, and query the actual data may be varied — and are not even prescribed by data mesh. Data fabric defined.

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business.