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About Austin Data Labs

Details: Our software eliminates the need to hire a team of data scientists in house. Annually, millions of dollars are spent on information acquisition, processing and storage, which in most cases are never used. Austin Data Labs was founded to meet this growing need for extracting value from the ever-increasing amount of high-quality data generated by labs in austin tx

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Austin Data Labs Insights

Details: Austin Data Labs Named One of Inc Magazine’s Best Workplaces 2022. Doing what we do at Austin Data Labs matters, and requires dedication. As the pandemic and climate change made the world’s food supply chain increasingly volatile over the last two years, our team stepped up to make sure our products were growing and adapting at a faster

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Winner: Best AI-based Data Science Solution, Austin Data Labs

Details: We’re so pleased to have been selected as a winner of the 2021 AI Breakthrough Award for Best AI-based Data Science Solution for our work in the global food supply chain!. You can read more about the award in our official press release here. “It’s expensive to build a data science team internally from scratch,” said James Johnson, managing director, AI Breakthrough.

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Master Data- The Hidden Anchor On Your Profits

Details: Companies undervalue master data. Why commodity companies tend to undervalue master data is a puzzle I’ve thought about deeply. One primary reason is that commodity companies are usually very cost conscious. Without robust data analysis and supply chain software, which many don’t have, they simply don’t see the need or the ROI.

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Tandem Implementation Of Your New ERP And Data

Details: Working with Austin Data Labs creates a smoother supply chain optimization project. When Austin Data Labs helps shape the ERP implementation from day one our customers have seen great success. For example, one recent project was performed in conjunction with a D365 implementation. We were able to perform a tight integration between …

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Meat Commodities

Details: Meat is a highly variable, living commodity influenced by a multitude of external factors beyond the farmer’s control. Meat demand is predictable, but prices for principal livestock production inputs are volatile. Using AI and advanced data science, you can prevent waste within your supply chain and recover lost value as you move your product

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Arquivos Data Science

Details: There is a concept that applying data science to your business will automate processes, consolidate information faster, make employees lives easier, and allow them to go home earlier. All of that is true! It does leave an important part out, however. What often doesn’t get mentioned is that data science comprehensively considers so many

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AgriTech Unconstrained: Complement Your SAP Solution

Details: You’re going to need to add in Austin Data Labs’ advanced data science working alongside your ERP for that. The 10 things you need to know. More ERP and SAP customers are choosing to complement their systems with data science products like ours at Austin Data Labs. Whether you need our products for planning or for your entire supply chain

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Data Science and AI can end your ERP horror story

Details: The right choice for volatile commodity supply chains is ERP + data science / AI. If you are looking to replace your existing ERP solution, we suggest you buy only the basics of the ERP you are interested in. Stay away from the “extra” modules like supply chain, demand planning, trade planning, transportation, and quality assurance.

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Why Does Enterprise IT Struggle To Put Together

Details: The data flow into analytics must be bi-directional. The level of skills required to utilize the SDAI should not exceed that of a good data analyst as the primary job of business users is to improve their businesses and not to build applications. And finally, the answer is not Excel. Excel does not scale, is difficult to share, does not process

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Master Your 3 Business Planning Horizons

Details: The mid-term planning horizon is less defined in most cases (and highly variable between companies) but is often thought of as 9-24 weeks, with some 9-52 week exceptions. Finally, the long term planning horizon is usually 1-3 years ahead. For this discussion we will focus on the different needs and challenges of these different time horizons.

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3 Examples of successful hybrid data science in the global food …

Details: At another customer, a unique, end-to-end, farm-to-market grocery chain, the divisions that are using our special blend of rules-based cooperation within their ERP in tandem with our data-science-based products are seeing solid returns. for example, they are seeing returns of more than 4% of sales in one of their meat divisions, and an overall

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Solving volatility with data science for the dairy industry

Details: This means your entire team has the right data at the right time to understand how it supports their experience and intuition and offer them a clear path – even when uncertainty is impacting everything from the dairy plant to the end products you create. It gets better. COVID-19 will pass, eventually, but volatility is here to stay.

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Dairy Commodities

Details: Unlock hidden value in your dairy production with machine learning and data science. Dairy products, like cheese, butter, and milk powder, create increased complexity as they flow through the commodity supply chain: each production decision creates multiple additional decisions and trade-offs. Further complexity is added by Mother Nature, with

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Can Data Science Help Fill Our Empty Shelves

Details: Data science can inform changes you make to your food shipping plans. The availability of cold storage trucks means that getting products around the country is now far more expensive than in the past (if you can even get a truck). This requires thinking out of the box when scheduling your logistics, as the old shipping rules of thumb no longer

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