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🚀 Highlights from the Databricks Data and AI Summit 2024 🚀 The #DAIS 24 was a whirlwind of non-stop action and innovations. Hugely grateful to the wonderful analyst relations team, Sonya Vargas (Ruzheva) and Kayli Berlin for another exceptionally well run event under the leadership of Joel Minnick . 🌟 We had the privilege of deeply interacting with Ali Ghodsi, Adam Conway, Rick Schultz, Ron Gabrisko, Arsalan Tavakoli, Raj Gossain and many other leaders. Their insights into the future of data transformation were nothing short of inspiring. I’ve distilled the key takeaways and my learnings into a new blog post. 👉 Read the full blog here: https://lnkd.in/gQn_D5As #DAIS24 #DataAISummit #DataTransformation #AI #ML #DBMS #Cloud #GenAI #LLM

Hiring SRE Engineers for multiple positions in Wilmington DE We are Looking for "Site Reliability Engineers With Java" Job Title: SRE Engineer With Java Location : Wilmington, DE(Hybrid 3 Days a Week) 9-12 Months Contract Ccube

Understanding Modern Data Management Architectures: Data Warehouse, Data Lake, Data Lake House, and Data Mesh In today’s data-driven world, understanding the right data architecture for your business is crucial. Here’s a simplified comparison of four prominent architectures: 1. Data Warehouse: A data warehouse is designed to store structured data, typically transformed through ETL (Extract, Transform, Load) processes. This structured approach ensures data consistency and is ideal for generating reports and visualizations using tools like Power BI. It’s perfect for businesses that rely on high-quality, reliable data for decision-making. 2. Data Lake: Data lakes take a more flexible approach, storing structured, semi-structured, and unstructured data. With robust data version control, data lakes support a wide range of applications, from data science to machine learning (ML) and reporting. This architecture is suitable for organizations needing to manage diverse data types and perform complex analytics. 3. Data Lake House: Combining the best of both data lakes and data warehouses, data lake houses offer a unified platform. They handle all types of data and include a metadata and governance layer to ensure data quality and compliance. This architecture supports everything from simple reporting to advanced analytics and ML, making it versatile for various data needs. 4. Data Mesh: The data mesh approach decentralizes data management, organizing data around specific business domains. Each domain is responsible for its own data, ensuring scalability and flexibility. This architecture includes a metadata and governance layer for consistency across the organization, supporting a wide range of data applications across different business units. Choosing the right architecture depends on your business’s specific needs, data types, and analytical requirements. Each of these solutions offers unique advantages, so understanding their core differences can help you make an informed decision for your data strategy. #DataManagement #DataWarehouse #DataLake #DataLakeHouse #DataMesh #BigData #Analytics #DataScience #MachineLearning #BusinessIntelligence

I’m #hiring. Know anyone who might be interested? 👋😊

Urgent requirement with Ccube Abinitio Developer Location: Columbus, OH (Day 1 Onsite) Long Term *** Local Candidates Highly Prefeerd*** Job Description: 7Years+ experience in IT industry strong data-warehouse and ETL - Abinitio background, along with hands on technical Excellent grasp on all Components of Ab Initio - GDE, PSETS, PDL Programming, Meta Programming, Webservices, Continuous Graphs and usage of Conduct>IT (Plans). Good experience in various Ab-initio parallelism techniques. Knowledge on Abinitio AIR commands and m commands and unix shell scripting. Knowledge of any database such as Oracle,Pl/Sql is a must. Must have knowledge on data warehousing concepts, knowledge on data modeling. Drive the architecture of a project, including authoring functional and design specifications, scalability, testing, quality data flow, and interface. Ability to Lead and Manage team and Interact with End users clients. Worked in Onsite/ Offshore model. Proficient in creating documentation related to design documents, Unit testing, handover and walk-through documents. Excellent analytical, interpersonal and leadership skills along with excellent oral and written communication skills. Working experience in Abinitio BRE Business Rule Environment or ACE Application   Configuration Environment is desirable: Desire to take ownership and run the show end to end Comfortable working with remote teams. Experience on AWS is a plus. Please share profiles at aman.verma@ccube.com #hiring #urgent #c2c #contract #w2 #1099 #columbus #ohio