Photo by Ramón Salinero on Unsplash Data scientists and data analysts are constantly required to answer questions for the business. This could result in a more ad-hoc analysis or some form of model that will be implemented into a company’s workflows. But to perform data science and analytics, teams first need access to quality data…
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Photo by Campaign Creators on Unsplash Information. Data. It’s always been the key to making good decisions. Whether you are a commander on a battlefield in 1000 BC or a CEO in a boardroom in 2000. Having critical information at the right time can make help make million and billion dollar decisions. But, just having…
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Photo by Margaret Weir on Unsplash One of the biggest roadblocks for data scientists looking to analyze data is getting access to that data. The data itself will need to be processed and placed into a central data system like a data warehouse or data lake. This is done by using what we call an…
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Photo by Yancy Min on Unsplash In this tech-centric era, companies aim to extract maximum business value from their data in order to stay relevant and efficient via data-driven business decisions. In order to do so, they rely on Artificial Intelligence and Machine Learning. In fact, research shows that artificial intelligence can increase business productivity by 40%! Therefore, it…
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Photo by Caspar Camille Rubin on Unsplash SQL remains the language for data. Developed back in the 1970s, it is one of the few technologies that has remained constant. Regardless of what drag and drop tools come around or what new query paradigms try to overtake it. SQL remains the most widely used technologies to interact with data.…
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Photo by Mr Cup / Fabien Barral on Unsplash SQL is one of the most in-demand technical skills in the workplace today. Developed back in the 1970s, it is still the way we interface most of our data systems today. Regardless of what drag and drop tools come around or what new query paradigms try…
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Photo by Startaê Team on Unsplash Our data consulting team has had the privileged to help develop strategies, data products, algorithms, upskill teams, and help grow our new data-focused departments at companies all across US. With all of this work focused around growing teams, data analytics strategies, and custom data science solutions we have…
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Photo by Shahadat Rahman on Unsplash With the increased need for data analytics and data science that is even more granular and allows for self-service analytics. Getting access to the data you need still is far from easy. If you have worked in any role related to data, or even just adjacent to it, you…
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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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