If you’re a small business or start-up, you’re probably reading articles about companies using data science, data analytics, and machine learning to increase their profits and reduce their costs. In fact, Mckinsey just came out with a study that found that the companies they survey could attribute 20% of their bottom line to AI implementations. All…
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Photo by Stephen Phillips – Hostreviews.co.uk on Unsplash You may have recently invested in Panoply to improve your team’s ability to access data. Panoply’s automated ELT process makes it really easy to integrate data from multiple sources including Salesforce, Workday, Asana, QuickBooks, and so many other tools into your company’s data warehouse. The simple GUI…
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When your team needs to create dashboards and metrics using data from external sources like Salesforce and MySQL, they face a difficult problem. How do they get all their data into one place in order to merge it all together? Traditionally you would need to have a large team of data engineers to connect to…
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The rise in self-service analytics is a significant selling point for data warehousing, automatic data integrations, and drag and drop dashboards. In fact, in 2020, the largest software IPO this year was a data warehousing company called Snowflake. The question is how do you get your data from external application data sources into a data…
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Photo by SpaceX on Unsplash Companies of all sizes are looking into implementing data science and machine learning into their products, strategies, and reporting. However, as companies start managing data science teams, they quickly realize there are a lot of challenges and inefficiencies that said teams face. Although it has been nearly a decade since…
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Photo by Lenin Estrada on Unsplash By Christopher Bowers Machine learning and automation are intrinsically intertwined in our world. Without automation, machine learning is reduced to making complex calculations by hand. Current levels of automation have tightened the machine learning life cycle and the integration of models into production. Not only are the tools to…
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Photo by Kaleidico on Unsplash Companies of all sizes have embraced using data to make decisions. However, according to a 2019 report from Goldman Sachs it’s actually quite difficult for businesses to use data to build a sustainable competitive advantage. Our team has worked with and for companies across industries. We have seen the good, the bad and the…
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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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We recently had a client ask us why they might want to build a data warehouse. They had several operational relational database and third parties like Salesforce. We saw clear ways that customers could benefit from a data warehouse. A data warehouse seemed like an appropriate fit for their uses cases they explained. They had…
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Photo by Eric Krull on Unsplash. Parsing and processing documents can provide a lot of value for almost every department in a company. This is one of the many use cases where natural language processing (or NLP) can come in handy. NLP is not just for chatbots and Gmail predicting what you are going to write in your…
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