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To make your data management processes easier, here’s a primer on datalakes, and our picks for a few datalake vendors worth considering. What is a datalake? First, a datalake is a centralized repository that allows users or an organization to store and analyze large volumes of data.
They are looking to engineer a proof-of-concept demo to start a company potentially. Building an Enterprise DataLake with Snowflake Data Cloud & Azure using the SDLS Framework. Articialpaulus has created a basic prototype demonstrating the potential of emotion prediction and word prediction models.
At the AI Expo and Demo Hall as part of ODSC West next week, you’ll have the opportunity to meet one-on-one with representatives from industry-leading organizations like Plot.ly, Google, Snowflake, Microsoft, and plenty more. Delphina Demo: AI-powered Data Scientist Jeremy Hermann | Co-founder at Delphina | Delphina.Ai
Many announcements at Strata centered on product integrations, with vendors closing the loop and turning tools into solutions, most notably: A Paxata-HDInsight solution demo, where Paxata showcased the general availability of its Adaptive Information Platform for Microsoft Azure. DataRobot Data Prep. free trial.
On Wednesday, Henk Boelman, Senior Cloud Advocate at Microsoft, spoke about the current landscape of Microsoft Azure, as well as some interesting use cases and recent developments. Expo Hall ODSC events are more than just data science training and networking events. You can read the recap here and watch the full keynote here.
At the AI Expo and Demo Hall as part of ODSC West in a few weeks, you’ll have the opportunity to meet one-on-one with representatives from industry-leading organizations like Microsoft Azure, Hewlett Packard, Iguazio, neo4j, Tangent Works, Qwak, Cloudera, and others.
Data analysts often must go out and find their data, process it, clean it, and get it ready for analysis. This pushes into Big Data as well, as many companies now have significant amounts of data and large datalakes that need analyzing. Cloud Services: Google Cloud Platform, AWS, Azure.
Microsoft Azure ML Platform The Azure Machine Learning platform provides a collaborative workspace that supports various programming languages and frameworks. It enables data scientists to log, compare, and visualize experiments, track code, hyperparameters, metrics, and outputs.
This typically involves dealing with complexities such as ensuring secure and simple access to internal data warehouses, datalakes, and databases. Some of the most widely adopted tools in this space are Deepnote , Amazon SageMaker , Google Vertex AI , and Azure Machine Learning. Aside neptune.ai
An ML platform standardizes the technology stack for your data team around best practices to reduce incidental complexities with machine learning and better enable teams across projects and workflows. We ask this during product demos, user and support calls, and on our MLOps LIVE podcast. Data engineers are mostly in charge of it.
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