A massive surge in unstructured data creates tough challenges for IT. Businesses need more intelligent network infrastructure to support their Big Data plans. The infographic below from XO Communications, highlights this need.
Industry Perspectives
Stop Building Models, Start Training Data
In this special guest feature, Sanjay Pichaiah, VP of Product Growth at Akridata, highlights why it is time for data scientists to stop building models and start training data. The path to better models and greater model accuracy doesn’t lie exclusively with the model, even though that has been the greatest focus in recent years. To truly accelerate and increase model performance, we need to be focusing more on the training data sets we are supplying the models and stop hoping the data is good enough.
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2022 State of Data Engineering: Emerging Challenges with Data Security & Quality
The 2022 Data Engineering Survey, from our friends over at Immuta, examined the changing landscape of data engineering and operations challenges, tools, and opportunities. The modern data engineering technology market is dynamic, driven by the tectonic shift from on-premise databases and BI tools to modern, cloud-based data platforms built on lakehouse architectures.
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