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Tag: data cleaning
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What are the challenges of creating a data product?
Data product development is hard. Really hard. It’s hard to come up with a good idea, it’s hard to build something people want to use, and it’s hard to keep the thing alive once it’s been released.
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The shift from data pipelines to data products
The shift from data pipelines to data products is a major trend in the industry today. Data products are more sophisticated and provide more value than data pipelines. They are the next step in the evolution of data management.
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Hur du får dina stakeholders att sluta tvivla och ifrågasätta vår data
Hur ofta har du fått ett meddelande från en stakeholder som säger att en dashboard är nere, data inte har uppdaterats på en vecka eller att specifika siffror ser fel ut? Detta har hänt alldeles för många gånger för att räknas. Varför är det så?
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#datapipeline: YouTube Analytics to BigQuery with Airbyte
You cannot simply rely on YouTube to derive maximum value for your business. It would be best if you combined YouTube and Google’s BigQuery to make more robust analytical insights and, in turn, drive increased revenue and growth to your YouTube channel. This data pipeline will demonstrate how you can easily leverage Airbyte to do…
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What is reverse ETL and why do you need it
Reverse ETL empowers data teams to easily prep bulk data, move it outside the cloud data warehouse, and operationalize it for their organization. Data is helpful, but its actual value is only realized when it is made actionable.
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What is Reverse ETL?
The data engineering industry has evolved from Extract, Transform, Load (ETL) to ELT, where raw data is copied from the source system loaded into a data warehouse or data lake and then transformed. The current trend is to adopt a new approach, called “reverse ETL,” the process of moving data from a data warehouse into third-party…
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List of datasets for all your data science work
Data science is a hot topic just now, more and more people are talking about it and planning to include data science in their organizations. The data science practice is to extract knowledge and insights from data and information generated through various tools and applications.
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List of modern data stack technologies for your modern data stack
We have created a list of modern data stack technologies. The Modern Data Stack technologies are mostly SaaS-based technologies that comprise runs on a cloud-native data platform, generally leveraged to reduce the complexity in running a traditional data platform. The goal with the Modern Data Stack is to make data actionable by reducing the time…
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#datapipeline the hourly electricity rate
I spent my Christmas holiday in the southern part of Sweden, the weather was cold with several days of temperatures down under -10 celsius. In the news were stories about new price records for a KwH of electricity. I started to get worried that our electricity bill for December or for the whole winter period…
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Data project: I became an environmental data collector
At the beginning of the Corona epidemic, I wrote an article about a personal data project I had worked on: The air I breathe how polluted is it?. After that project, I became an environmental data collector by purchasing a wearable, portable indoor-outdoor air quality monitor. My interest in air quality is about the fact that…