Data Warehousing: Everything You Need to Know When Assessing Data Warehousing Skills

Data Warehousing

Data warehousing is the process of collecting, transforming, and storing data from multiple sources into a single central repository. The goal of data warehousing is to create a single source of truth for data, which can be used for business intelligence and analytics.

Data warehouses typically store historical data, but they can also store real-time data. Data warehouses are often used to store data from a variety of sources, such as transactional systems, customer relationship management (CRM) systems, and enterprise resource planning (ERP) systems.

Data warehousing systems are designed to support complex queries and analytics. Data warehouses often use specialized data structures and algorithms to improve query performance. Data warehouses can also be used to build machine learning models and to perform other types of advanced data analysis.

Here are some of the benefits of using data warehousing:

Improved data quality: Data warehouses can help to improve data quality by centralizing and cleansing data from multiple sources.
Increased data accessibility: Data warehouses make it easier for users to access and analyze data from multiple sources.
Improved performance: Data warehouses are designed to support complex queries and analytics with high performance.
Reduced costs: Data warehouses can help to reduce costs by centralizing data and eliminating the need to replicate data across multiple systems.

Data warehousing is an important tool for businesses of all sizes. By creating a single source of truth for data, businesses can improve their decision-making and gain a competitive advantage.

Here are some examples of how data warehousing is used in different industries:

Retail: Retailers use data warehouses to track sales trends, identify customer segments, and optimize marketing campaigns.
Finance: Financial institutions use data warehouses to manage risk, track compliance, and develop new financial products.
Healthcare: Healthcare providers use data warehouses to track patient outcomes, identify disease outbreaks, and develop new treatments.
Manufacturing: Manufacturers use data warehouses to optimize production schedules, improve quality control, and reduce costs.

Data warehousing is a powerful tool that can be used to improve business intelligence and analytics. By creating a single source of truth for data, businesses can make better decisions and gain a competitive advantage.

Discover How To Get Started Assessing Data Warehousing Skills

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Scott Crowe, Canva (Lead Recruiter - Data)

How can you accurately assess somebody's technical skills, like the same way across the board, right? We had devised a Tableau-based assessment. So it wasn't like a past/fail. It was kind of like, hey, what do they send us? Did they understand the data or the values that they're showing accurate? Where we'd say, hey, here's the credentials to access the data set. And it just wasn't really a scalable way to assess technical - just administering it, all of it was manual, but the whole process sucked!

Cole Brickley, Avicado (Director Data Science & Business Intelligence)

I wouldn't dream of hiring somebody in a technical role without doing that technical assessment because the number of times where I've had candidates either on paper on the CV, say, I'm a SQL expert or in an interview, saying, I'm brilliant at Excel, I'm brilliant at this. And you actually put them in front of a computer, say, do this task. And some people really struggle. So you have to have that technical assessment.

Mike Yates, The British Psychological Society (Head of Data & Analytics)

I was at WooliesX (Woolworths) and we used Alooba and it was a highly positive experience. We had a large number of candidates. At WooliesX, previously we were quite dependent on the designed test from the team leads. That was quite a manual process. We realised it would take too much time from us. The time saving is great. Even spending 15 minutes per candidate with a manual test would be huge - hours per week, but with Alooba we just see the numbers immediately.

Shen Liu, Logickube (Principal at Logickube)

We get a high flow of applicants, which leads to potentially longer lead times, causing delays in the pipelines which can lead to missing out on good candidates. Alooba supports both speed and quality. The speed to return to candidates gives us a competitive advantage. Alooba provides a higher level of confidence in the people coming through the pipeline with less time spent interviewing unqualified candidates.

Scott Crowe, Canva (Lead Recruiter - Data)

How can you accurately assess somebody's technical skills, like the same way across the board, right? We had devised a Tableau-based assessment. So it wasn't like a past/fail. It was kind of like, hey, what do they send us? Did they understand the data or the values that they're showing accurate? Where we'd say, hey, here's the credentials to access the data set. And it just wasn't really a scalable way to assess technical - just administering it, all of it was manual, but the whole process sucked!

Cole Brickley, Avicado (Director Data Science & Business Intelligence)

I wouldn't dream of hiring somebody in a technical role without doing that technical assessment because the number of times where I've had candidates either on paper on the CV, say, I'm a SQL expert or in an interview, saying, I'm brilliant at Excel, I'm brilliant at this. And you actually put them in front of a computer, say, do this task. And some people really struggle. So you have to have that technical assessment.

Mike Yates, The British Psychological Society (Head of Data & Analytics)

I was at WooliesX (Woolworths) and we used Alooba and it was a highly positive experience. We had a large number of candidates. At WooliesX, previously we were quite dependent on the designed test from the team leads. That was quite a manual process. We realised it would take too much time from us. The time saving is great. Even spending 15 minutes per candidate with a manual test would be huge - hours per week, but with Alooba we just see the numbers immediately.

Shen Liu, Logickube (Principal at Logickube)