Photo by bruce mars on Unsplash Technology has been speeding forward through 2020. The impacts of Covid have only sped up the adoption of change for companies. Companies small and big, start-ups and corporations have been pushed to innovate and improve processes. For example, small, medium, and large companies are migrating to the cloud to…
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Even small companies these days on average have 47.81 terabytes of data that they manage. Regardless if you’re a small company or a trillion-dollar behemoth, data is driving decisions. But as data ecosystems become more complex, having the right tools for the job is important. One modern data management tool that can help manage data at really…
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Did you know that $28.5 billion were spent on investing in machine learning projects, tools, and employees in 2019? Machine learning has taken over pretty much every industry, owing to the automation and flexibility it is bringing to work. Companies of all sizes are using machine learning tools and cloud services. Services like AWS Comprehend and other similar…
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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 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 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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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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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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