Asim Lilani

Snowflake: Iceberg Dynamic Tables https://lnkd.in/gtCpgHgu

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⛑️☁️ Preview on how Epic Cogito Cloud on Microsoft Fabric will be able to work with Snowflake without copying data: "This will enable our joint customers to experience bidirectional data access between Snowflake and Microsoft Fabric, with a single copy of data with OneLake in Fabric. Organizations using both platforms will be able to do so more cost-effectively, rather than building pipelines or maintaining copies of data in each platform." - Christian Kleinerman ❄️ #interoperability #datacloud #apacheiceberg #apachextable #fabric #msfabric #epic #epiccogito #cogitocloud #clarity #caboodle #nebula #epicnebula #snowflake #onelake #aidatacloud #aiml #healthcare #healthIT #hcldr #hitsm #healthtech

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👀 This is gold and super top of mind for so many enterprises. They want to modernize their Databricks + Snowflake investment so that they aren’t needlessly moving/duplicating data, aren’t double-dipping compute, and are moving towards the trend of open standards and table-formats. 💪🔥

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📓 Quick Read: In this post, Jon Alkan provides an overview of 3 Snowflake performance features: (1) Search Optimization Service, (2) Query Acceleration Service, and (3) Cache.

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Informatica's GenAI assistant for data management is now GA💥 This will be an ideal case study for the risks and rewards of domain-specific GenAI. The rewards: more productive data teams, more accurate and more timely data to drive analytics. The risks: hallucinations, PII exposure, broken data pipelines. Informatica comes at this from a point of strength - broad portfolio, deep installed base, lots of metadata to train GenAI language models. Gaurav Pathak gave a compelling introduction and demo here at Informatica World. The stakes are high. Check out this article by Eric Avidon of TechTarget to learn more. Excerpts below. https://lnkd.in/gkrb3eRd "Informatica unveiled Claire CGPT and the low-code/no-code development interface during Informatica World, the vendor's annual user conference in Las Vegas. "Now, Claire GPT is generally available while the and the low-code/no-code development interface is in preview. Both make it easier to use a platform that plays an important role in helping organizations manage and operationalize data and are therefore significant, according to Stephen Catanzano, an analyst at TechTarget's Enterprise Strategy Group. "Kevin Petrie, an analyst at BARC U.S., noted that Claire has enabled data teams to prepare and govern data with automation, AI and metadata since it was first released seven years ago. Claire GPT builds on Claire's capabilities. "This announcement extends the role of GenAI within Claire -- a vision they articulated last year -- by using a natural language interface to handle commands that previously required mouse clicks or manual scripting," Petrie said. "Beyond addressing ease-of-use and productivity like many generative AI assistants, Claire GPT has the potential to be more accurate than some other natural language tools given Informatica's access to metadata, he continued. "Informatica's extensive installed base gives it a rich metadata repository on which it can train and fine-tune GenAI language models," he said. "This differentiates Informatica because they can produce models that are less likely to hallucinate, expose sensitive data or cause other governance issues." "Petrie, however, cautioned that although the low-code/no-code interface for generative AI development is compelling and addresses a real need, trained experts will still need to be involved in the application development process. "The tool will still require expert human oversight," he said. "Data engineers, data stewards, or business-oriented data consumers will need to carefully inspect the quality of outputs they get from these language models before they put anything into production. "The caveat of data democratization [is that] you still need … experts to ensure the artifacts and data outputs are trustworthy." Shawn Rogers Timm Grosser Ankur G. Sarath Chunchu Suresh Thottempudi #data #genai #informaticaworld

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We did some investigation on JDBC connectors to Salesforce and pricing was ridiculous from multiple vendors. I could employ an FTE for what they were asking. In the age of LLMs, why not just use your new coding assistant to create your own API driven connector? A good example of how LLMs could drive the cost of software down and allow you to invest more in people that can do more because of language models. 😀 Direct queries to Salesforce from Exasol:

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Bi-directional data access between Snowflake and Fabric offers an exciting partnership. I assume this brings enhanced interoperability, reduced complexity and costs, increased access to tools and applications, and improved data insights. Excited to hear of any Snowflake announcements at the Summit. #Snowflake

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If you are a customer of Snowflake and Salesforce this integration is game changing. Deeper integration = more ROI as illustrated via 3 industry use case examples below. Data is only valuable to the Business if it’s Accessible, Actionable & can be used in the front office: 💪 Retailers can use Commerce and Service Cloud data w/ POS and supply chain in Snowflake 💪 CPGs can organize Marketing and Sales Cloud in Data Cloud w/ financial and transaction data in Snowflake; and share data via clean room 💪 Media orgs can use 1P data in Data Cloud to power media campaigns via Snowflake clean rooms or Data Cloud ad activations

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#DatabricksSQL warehouses provide up to 12x improved price performance over standard interactive clusters. You can now use Databricks Notebooks on SQL Warehouses to write and schedule Git-backed, multi-statement, and parameterized SQL👇 https://dbricks.co/4agOeJo

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I think todays announcement of Datavolo acquisition is a drop the mic moment for Snowflake in terms of building #data #pipelines. Quick research shows #Datavolo is an #AI driven Low/No code ETL tool based on #OSS Apache NiFi which can build both structured and unstructured data pipelines within minutes by simply users describing the pipeline they need in plain English. Imagine you asking "Build a pipeline that ingest JSON files from S3 bucket called 'XYZ' into a table called FOO in the TESTDB Database where the files may be compressed. Modify the date format in ColX from MM/YY to YYYY-MM" and this thing builds an entire #NIFI data pipeline workflow within seconds where you can make modifications later on if necessary. I have no idea how Snowflake plans to implement it but if this is close to how it may work in the product, it will be a total game changer for #dataengineering for #datawarehousing & #GenAI use cases. It will literally accelerate onboarding new data sources from weeks to minutes while allowing our customers to not just ingest + tranform/process structured & semi-structured data but also unstructured data as well for new GenAI use cases from hundreds of sources with built-in connectors. Needless to say, I am super excited & can't wait to get my hands on it once they incorporate it in to the product. God Speed!!! Check out these quick demos: Ingesting JSON to Snowflake https://lnkd.in/gJM7xXb2 Prepping Docs in Google Drive for a RAG application: https://lnkd.in/gQi_K4n9

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Still buzzing from an exciting week in San Francisco at the Databricks Data and AI Summit. This article gives a good summary of the biggest announcements from Wednesday's keynote (LakeFlow was on Thursday's keynote list).

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A step further in delivering scalable, high-performance data solutions. For organizations looking to stay competitive, leveraging Databricks is no longer optional — it’s a necessity. #STRATEDGE #dataengineering #BusinessIntelligence #data

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More learning on a topic that I'm helping an Oracle customer move data to with #goldengate. #bigdata #cloud #snowflake #customersuccess #dataengineer #data #platforms

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Qlik's associative engine is still one of the most powerful tools for insight. I am happy to see it is still getting attention - I'll be tuning in to this episode of #InsideAnalysis for sure.

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Please read my latest post, which demonstrates how to prepare and vectorize your data in 23ai so you can perform powerful Vector/Semantic-based searches in APEX #orclAPEX #23ai #vectorsearch #semanticsearch https://lnkd.in/gfHhpkuN

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Collibra + Databricks enable simplified Data Quality for organizations to benefit from out of the box capability. Get your data ready for the AI journey by leveraging this powerful solution.

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Wouldn't it be nice to query your data warehouse using natural language (e.g., show me YTD revenues for the Northeast Region for Products ABC and XYZ)? The large LLM's like like OpenAI, Cohere and Azure OpenAI support this use case but it must be hard to set all this up and get it working - right? Well, not necessarily. With just a little configuration, Oracle's Select AI capability enables popular LLM's to be leveraged to convert natural language text into SQL queries. The short blog below explains how this works. https://lnkd.in/edXuhyBt #texttosql #GenAI #OpenAI #Cohere #APAX #SelectAI

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An interesting and relevant repost by Ian Coyle Data Ideology, LLC. The competition between Databricks and Snowflake isn't a zero-sum game. Do you agree? #HealthcareData #HealthcareAnalytics #AIinHealthcare #HealthcareInnovation #DigitalHealth #HealthTech #HealthcareTransformation #HealthDataGovernance #ValueBasedCare #DataDrivenHealthcare #PopulationHealth #HealthIT #HealthcareAI #DataScienceInHealthcare #HealthcareQuality #Snowflake #Databricks #Teradata

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