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10 Cheat Sheets You Need To Ace Data Science Interview

KDnuggets

The only cheat you need for a job interview and data professional life. It includes SQL, web scraping, statistics, data wrangling and visualization, business intelligence, machine learning, deep learning, NLP, and super cheat sheets.

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Navigate your way to success – Top 10 data science careers to pursue in 2023

Data Science Dojo

Business Intelligence Analyst Business intelligence analysts are responsible for gathering and analyzing data to drive strategic decision-making. They require strong analytical skills, knowledge of data modeling, and expertise in business intelligence tools.

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Data science vs data analytics: Unpacking the differences

IBM Journey to AI blog

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. They may also use tools such as Excel to sort, calculate and visualize data.

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The Top Ten Certifications For Data Analysts

Pickl AI

Are you aiming for an entry-level role or looking to specialise in a particular area of Data Analytics, such as Machine Learning or Business Intelligence? The syllabus is thoughtfully structured to cover essential Data Analysis techniques, empowering students to tackle complex problems.

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Is Data Science Hard? Unveiling the Truth About Its Complexity!

Pickl AI

Data Wrangling The process of cleaning and preparing raw data for analysis—often referred to as “ data wrangling “—is time-consuming and requires attention to detail. Ensuring data quality is vital for producing reliable results.

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Five benefits of a data catalog

IBM Journey to AI blog

Let’s look at five benefits of an enterprise data catalog and how they make Alex’s workflow more efficient and her data-driven analysis more informed and relevant. A data catalog replaces tedious request and data-wrangling processes with a fast and seamless user experience to manage and access data products.

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How to Shift from Data Science to Data Engineering

ODSC - Open Data Science

Data scientists typically have strong skills in areas such as Python, R, statistics, machine learning, and data analysis. Believe it or not, these skills are valuable in data engineering for data wrangling, model deployment, and understanding data pipelines.