This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
In this episode Crux CTO Mark Etherington discusses the different costs involved in managing external data, how to think about the total return on investment for your data, and how the Crux platform is architected to reduce the toil involved in managing third party data. Tired of deploying bad data?
Summary With the proliferation of data sources to give a more comprehensive view of the information critical to your business it is even more important to have a canonical view of the entities that you care about. Request a demo at dataengineeringpodcast.com/metis-machine to learn more about how Metis Machine is operationalizing data science.
Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Datamanagement recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.
LLMs with Keras — Keras team demoed various workflows around LLMs (Gemma) with Keras. Opt-out to avoid Slack training LLM models on your private data — Slack (acquired by Salesforce) could train their LLM models on your data. This is close to what I had demoed last year in a talk. This is pure gold.
In this episode he shares his thoughts on the strategic and tactical elements of moving your work as a data professional from being task-oriented to being product-oriented and the long term improvements in your productivity that it provides. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold.
Let’s take a look at a few examples of Snowflake Native Apps that utilize Snowpark Container Services: Carto: Carto, a geospatial platform, can be deployed entirely inside Snowflake to tackle problems like vehicle routing without requiring data movement. Check out the demo. Check out the demo and sign up for the waitlist.
In our previous post, The Pros and Cons of Leading DataManagement and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a datamanagement ecosystem?
In our previous post, The Pros and Cons of Leading DataManagement and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a datamanagement ecosystem?
In our previous post, The Pros and Cons of Leading DataManagement and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a datamanagement ecosystem?
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you're ready to build your next pipeline, or want to test out the projects you hear about on the show, you'll need somewhere to deploy it, so check out our friends at Linode.
Upgraded Data Governance service Artificial intelligence (AI) advancements Expanded data integration capabilities Enhanced Data Catalog functionality Together, these advancements enable your organization to better integrate, govern, and improve the readiness of your data for trusted analytics, reliable AI insights , and faster time to value.
In this episode she shares the story behind the project, the details of how it is implemented, and how you can use it for your own data projects. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Who is the target audience for Zingg?
Leading companies around the world rely on Informatica datamanagement solutions to manage and integrate data across various platforms from virtually any data source and on any cloud. Enterprise Data Integrator is fueled by Informatica Superpipe for Snowflake, which enables up to 3.5x
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.
In this episode CEO and founder Salma Bakouk shares her views on the causes and impacts of "data entropy" and how you can tame it before it leads to failures. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.
Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are datamanagement and storage solutions designed to meet different needs in data analytics, integration, and processing. See it in action and schedule a demo with one of our data experts today.
Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are datamanagement and storage solutions designed to meet different needs in data analytics, integration, and processing. See it in action and schedule a demo with one of our data experts today.
Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are datamanagement and storage solutions designed to meet different needs in data analytics, integration, and processing. See it in action and schedule a demo with one of our data experts today.
Public, private, hybrid or on-premise datamanagement platform. Analytics that are simple to use and manage for actionable insights. Structure for unstructured data sources such as clinical & physician notes, photos, etc. Security and governance in a hybrid environment. Lunch and refreshments will be provided.
If you are starting down the path of implementing a data governance strategy then this episode will provide a great overview of what is involved. If you hand a book to a new data engineer, what wisdom would you add to it? What is data governance? If you hand a book to a new data engineer, what wisdom would you add to it?
In this episode Isaac Brodsky explains how the Unfolded platform is architected, their experience joining the team at Foursquare, and how you can start using it for analyzing your spatial data today. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.
In this episode he shares his experiences working with organizations to adopt analytics engineering patterns and the ways that Optimus and dbt were combined to let data analysts deliver insights without the roadblocks of complex pipeline management. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold.
Their analytics-first approach to healthcare leverages AI-powered insights and workflows through natively integrated datamanagement, analytics and care management solutions. Leap Metrics Leap Metrics is a SaaS company that seeks to improve health outcomes for populations with chronic conditions while reducing the cost of care.
How to chat with data in Snowflake using ChatGPT, dbt, and Streamlit — Less boring, obviously when you put ChatGPT and dbt in the same sentence it creates buzz instantly. This is an interesting demo of how you can quickly build a chat experience—using OpenAI—on top of you data models.
We’ll also provide demo code so you can try it out for yourself. The explosive number of devices generating, tracking and sharing data across a variety of networks is overwhelming to most datamanagement solutions. Demo of Scylla and Confluent integration. We will be interacting with the data in Kafka via KSQL.
Preamble Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline you’ll need somewhere to deploy it, so check out Linode. What is unique about customer event data from an ingestion and processing perspective?
They also explain some of the types of data that you can use with Chaos Search, how to load it into S3, and when you might want to choose it over Amazon Athena for our serverless data analysis. Request a demo at dataengineeringpodcast.com/metis-machine to learn more about how Metis Machine is operationalizing data science.
This is a great episode to listen to for ideas on how to organize a data engineering organization. Preamble Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline you’ll need somewhere to deploy it, so check out Linode.
This was a deep dive on how to build a successful company around a powerful platform, and how that platform simplifies operations for enterprise grade datamanagement. Request a demo at dataengineeringpodcast.com/metis-machine to learn more about how Metis Machine is operationalizing data science.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.
He also explains which layers are useful for the different members of the business, and which pitfalls to look out for along the path to a mature and flexible data platform. Request a demo at dataengineeringpodcast.com/metis-machine to learn more about how Metis Machine is operationalizing data science.
If you need to deal with massive data, at high velocities, in milliseconds, then Aerospike is definitely worth learning about. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Can you describe what Aerospike is and the story behind it?
In this episode Prineha Narang, co-founder and CTO of Aliro, explains how these systems work, the capabilities that they can offer, and how you can start preparing for a post-quantum future for your data systems. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold.
Like technical debt, data debt represents the liability accrued over time by inefficient and outdated methods and technologies for handling corporate data. It is important to note that data debt has methodological and technological components. Datamanagement technologies grow old and out of date.
And if you’re looking to get your own personalized demo of ThoughtSpot Sage, we hope you’ll stop by our booth, #2300 at Snowflake Summit 2023. Read more about our approach to safe-reliable self-service analytics powered by GPT and try ThoughtSpot free for 30-days via Snowflake Partner Connect.
This efficiency doesn’t just speed things up; it fundamentally changes how swiftly and effectively you can harness the power of your data assets. This approach doesn’t just solve existing problems; it paves the way for a new era of efficiency and effectiveness in datamanagement.
Adding more wires and throwing more compute hardware to the problem is simply not viable considering the cost and complexities of today’s connected cars or the additional demands designed into electric cars (like battery management systems and eco-trip planning).
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.
If you are struggling with inconsistent implementations of event data collection, lack of clarity on what attributes are needed, and how it is being used then this is definitely a conversation worth following. If you hand a book to a new data engineer, what wisdom would you add to it? Closing Announcements Thank you for listening!
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. How is Pinecone implemented?
It was an interesting conversation about how he stress tested the Instaclustr managed service for benchmarking an application that has real-world utility. Contact Info LinkedIn @paulbrebner_ on Twitter Parting Question From your perspective, what is the biggest gap in the tooling or technology for datamanagement today?
Announcements Hello and welcome to the Data Engineering Podcast, the show about modern datamanagement When you're ready to build your next pipeline, or want to test out the projects you hear about on the show, you'll need somewhere to deploy it, so check out our friends at Linode. Rudderstack : ![Rudderstack]([link]
Summary As more organizations are gaining experience with datamanagement and incorporating analytics into their decision making, their next move is to adopt machine learning. By empowering data teams with end-to-end data reliability, Monte Carlo helps organizations save time, increase revenue, and restore trust in their data.
We organize all of the trending information in your field so you don't have to. Join 37,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content