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

Data Streaming

Data streaming is the process of continuously receiving and processing data as it is generated. This is in contrast to traditional batch processing, where data is collected and processed in batches. Data streaming is becoming increasingly important as businesses generate more and more data in real time.

Data streaming can be used for a variety of purposes, including:

Real-time analytics: Data streaming can be used to analyze data as it is generated, which can provide businesses with real-time insights into their operations. For example, a retail company could use data streaming to analyze customer purchase data in real time to identify trends and patterns.
Fraud detection: Data streaming can be used to detect fraudulent transactions as they occur. For example, a bank could use data streaming to monitor account activity for suspicious activity.
Predictive maintenance: Data streaming can be used to predict when equipment is likely to fail, which can help businesses avoid costly downtime. For example, a manufacturing company could use data streaming to monitor equipment performance and identify potential problems before they occur.

Data streaming offers a number of benefits over traditional batch processing, including:

Real-time insights: Data streaming can provide businesses with real-time insights into their operations, which can help them make better decisions faster.
Reduced latency: Data streaming can reduce the latency between data generation and analysis, which can be critical for applications such as fraud detection and predictive maintenance.
Scalability: Data streaming is inherently scalable, which means that it can handle large volumes of data without sacrificing performance.

Data streaming is used in a wide variety of industries, including:

Retail: Retailers use data streaming to analyze customer purchase data in real time to identify trends and patterns. This information can be used to improve product placement, marketing campaigns, and inventory management.
Financial services: Financial services companies use data streaming to detect fraudulent transactions, monitor customer risk profiles, and provide real-time market data.
Manufacturing: Manufacturers use data streaming to monitor equipment performance, predict maintenance needs, and optimize production processes.
Transportation: Transportation companies use data streaming to track vehicle locations, optimize traffic flow, and manage fuel consumption.
Healthcare: Healthcare organizations use data streaming to monitor patient vital signs, track the spread of diseases, and provide personalized care.

Data streaming is a powerful technology that can help businesses make better decisions faster. It is becoming increasingly important as businesses generate more and more data in real time. If you are looking for a way to improve your business operations, data streaming is a good place to start.

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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)