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chaossearch

Databases Compared: Databricks vs. Snowflake vs. ChaosSearch vs. Elasticsearch

May 16, 2024 By David Bunting In ChaosSearch
For organizations that generate large amounts of data, implementing a cloud database solution is a critical step towards enabling performant and cost-effective data storage, transformation, and analytics. Choosing the right cloud database solution involves careful consideration of features, capabilities, costs, and use cases to ensure alignment with your organization’s needs and objectives. This blog post features an in-depth comparison of four popular cloud database solutions: Databricks vs.
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Product Update: Boost Databricks productivity, performance, and efficiency

May 16, 2024 By Unravel In Unravel
Today, 65% of IT decision-makers believe their company is falling behind the competition in using data and analytics. Why? Organizations want real-time insights, fraud/anomaly detection, trend analysis, and systems monitoring. The good news – data teams that use DataOps practices and tools will be 10 times more productive.With this in mind, Unravel is hosting a live event to share new capabilities to help you achieve productivity, performance, and cost efficiency with Databricks’ Data Intelligence Platform.
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confluent

Contributing to Apache Kafka: How to Write a KIP

May 16, 2024 By Lucia Cerchie In Confluent
I’m brand new to writing KIPs (Kafka Improvement Proposals). I’ve written two so far, and my hands sweat every time I hit send on an email with ‘ KIP’ in the title. But I’ve also learned a lot from the process: about Apache Kafka internals, the process of writing KIPs, the Kafka community, and the most important motivation for developing software: our end users. What did I actually write? Let’s review KIP-941 and KIP-1020.
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snowflake

Snowflake Arctic Cookbook Series: Instruction-Tuning Arctic

May 16, 2024 By Snowflake AI Research In Snowflake
On April 24, we released Snowflake Arctic with a key goal in mind: to be truly open. In line with that goal, the Snowflake AI Research team is writing a series of cookbooks to describe how to pretrain, fine-tune, evaluate, and serve large-scale mixture-of-experts (MoEs) such as Arctic.
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hitachi vantara

Hitachi Vantara and Veeam Form Global Strategic Alliance to Deliver Comprehensive Data Protection Solutions for Hybrid Cloud

May 15, 2024 By Hitachi Vantara In Hitachi Vantara
New partnership reinforces Hitachi Vantara defense-in-depth strategic approach, combining company's infrastructure expertise with Veeam's data protection and ransomware recovery software.
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astera

What Is Metadata Why Is It Important?

May 15, 2024 By Saba Jahangir In Astera
Metadata refers to the information about data that gives it more context and relevance. It records essential aspects of the data (e.g., date, size, ownership, data type, or other data sources) to help users discover, identify, understand, organize, retrieve, and use it—transforming information into business-critical assets. Think of it as labels on a box that describe what’s inside. Metadata makes it easier to find and utilize the data that you need. Typical metadata elements include.
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snowflake

5 Ways Advertising, Media and Entertainment Companies are Using Gen AI

May 15, 2024 By Snowflake In Snowflake
The emergence of generative AI (gen AI) heralds a new, groundbreaking era for advertising, media and entertainment. According to a recent Snowflake report, Advertising, Media and Entertainment Data + AI Predictions 2024, gen AI is going to transform the industry — from content creation to customer experience. The companies that will come out ahead during this time are those that most successfully and quickly supercharge their data strategy.
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astera

Exploring Data Provenance: Ensuring Data Integrity and Authenticity

May 15, 2024 By Zoha Shakoor In Astera
Data provenance is a method of creating a documented trail that accounts for data’s origin, creation, movement, and dissemination. It involves storing the ownership and process history of data objects to answer questions like, “When was data created?”, “Who created the data?” and “Why was it created? Data Provenance is vital in establishing data lineage, which is essential for validating, debugging, auditing, and evaluating data quality and determining data reliability.
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cloudera

What Separates Hybrid Cloud and 'True' Hybrid Cloud?

May 14, 2024 By Wim Stoop In Cloudera
Hybrid cloud plays a central role in many of today’s emerging innovations—most notably artificial intelligence (AI) and other emerging technologies that create new business value and improve operational efficiencies. But getting there requires data, and a lot of it. More than that, though, harnessing the potential of these technologies requires quality data—without it, the output from an AI implementation can end up inefficient or wholly inaccurate.
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