Automating daily tasks with Python is easy. With a combination of APIs and easy-to-understand libraries, you can easily set up systems that scrape websites, send emails, and manage data and analytics. One very common task you’ll need to automate in the corporate world is the ability to scrape public government data. This usually comes from…
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As a developer, you will often need to create APIs to interact with various systems and integrations. Traditionally, this required a lot of work as far as developing the infrastructure and deploying the code on either an on-premise or cloud server like EC2. However, this method is slow and costly. Thus, the concept of serverless…
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Photo by ev on Unsplash There are plenty of cliches about data and its likeness to oil or companies being data-driven. Is there truth to all this hype about data strategy, predictive modeling, data visualization, and machine learning? In our experience, these cliches are true. In the past few years, we have already helped several…
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With success accompanying a growing brand comes the demand for better technological solutions. Businesses today consider full access to specialized support services like cloud computing an integral part of their day to day. Cloud computing permits firms to access to the same computing power that big businesses have. Cloud computing also delivers the perfect fit…
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Photo by Mike Benna on Unsplash One of the main roles of a data engineer can be summed up as getting data from point A to point B. We often need to pull data out of one system and insert it into another. This could be for various purposes. This includes analytics, integrations, and machine learning. But in…
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Ready to unlock your company’s potential using data? Data automation and visualization is your answer. And here at the Seattle Data Guy, we’ve got you covered. Companies from Seattle to New York trust us with their data science solutions. Why’s that? The short answer: while many companies have been leveraging data science and…
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Photo by Science in HD on Unsplash Unlike software engineering, there aren’t a lot of college courses in data engineering. Nor a huge list of boot camps teaching the practice. This leads to best practices often being learned on the job, as well as a cornucopia of technologies being used across teams and companies. So what defines a…
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Photo by Levi Jones on Unsplash A vital part of the successful completion of any project is the selection of the right tools. When it comes to big data, sometimes the difficult choice here is picking the right streaming data service. For example should you use Apache Kafka or RabbitMQ. Both platforms feature several functionalities and use cases…
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Photo by Nathan John on Unsplash Managing big data no longer means just buying bigger and faster servers It now also means needing to understand the concept of parallel computing. The list of tools and data systems that are helping manage this specific concept continues to grow on a yearly basis. Whether it be using AWS and querying…
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Photo by Sean Pollock on Unsplash Banks from Seattle to New York trust us with their data science solutions. Why’s that? The short answer: while the finance industry has been leveraging data science and statistics for decades, times are changing. Data science and financial strategy are evolving. This means teams need to stay current in order to maximize…
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