Techelligence, Inc

Techelligence, Inc

IT Services and IT Consulting

Atlanta, Georgia 29,561 followers

Data AI Company specializing in providing solutions leveraging the Databricks ecosystem

About us

Welcome to the forefront of data innovation with Techelligence, the premier consulting firm specializing in harnessing the full potential of the Databricks ecosystem. We are the architects of data transformation, dedicated to empowering businesses to make the most of their data assets. At Techelligence, we understand that data is the lifeblood of modern business. Our team of seasoned experts is committed to providing tailored solutions that unlock the power of Databricks' unified platform for data engineering, analytics, and AI. Whether you're looking to modernize your data infrastructure, optimize machine learning models, or enhance data governance, we've got you covered. With a deep understanding of the Databricks ecosystem, we offer a comprehensive suite of services designed to drive business growth and innovation. From strategic planning and architecture design to implementation and ongoing support, our consultants work hand-in-hand with your team to ensure seamless integration and maximum ROI. Partnering with Techelligence means gaining access to a wealth of expertise and a proven track record of success. We pride ourselves on staying at the cutting edge of data and AI technology, so you can focus on what matters most: driving your business forward. Our team of experts has a deep understanding of the Databricks ecosystem, allowing us to utilize Mosaic AI to its fullest potential. We are adept at fine-tuning foundation models, integrating them with your enterprise data, and augmenting them with real-time data to deliver highly accurate and contextually relevant responses. Choose Techelligence as your trusted partner in navigating the complex world of data and AI. Together, we'll unlock the full potential of your data and set you on the path to becoming a true data-driven organization. With over 85 consultants, we can take on any project - big or small! We are a Registered Databricks Partner!

Website
https://techelligence.com/
Industry
IT Services and IT Consulting
Company size
11-50 employees
Headquarters
Atlanta, Georgia
Type
Privately Held
Founded
2018
Specialties
Data Strategy, Databricks , Azure, AWS, GenAI, and Data Engineering

Locations

  • Primary

    1349 W Peachtree St NE

    #1910

    Atlanta, Georgia 30309, US

    Get directions

Updates

  • View organization page for Techelligence, Inc, graphic

    29,561 followers

    View organization page for Data Works, graphic

    119,423 followers

    Are you using the full potential of your data science learning journey? Discover the four essential methodologies—Transfer Learning, Fine-tuning, Multi-task Learning, and Federated Learning—that can elevate your machine learning models from good to exceptional. Whether you're dealing with limited data, optimizing models for multiple tasks, or ensuring privacy with federated learning, these approaches are your gateway to more powerful and efficient AI solutions. Dive deep into these concepts and see how they can transform your data science projects. Ready to take your machine learning skills to the next level? Credits: Daily Dose of Data Science

  • View organization page for Techelligence, Inc, graphic

    29,561 followers

    Great info if you want to learn about Generative AI terminologies! #generativeai #llm #learning #knowledge

    View profile for Sourav Banerjee, graphic

    Senior Solutions Consultant @ Databricks| 4X Microsoft Azure Certified| 6X Databricks Certified| Spark| Databricks| Streaming | Kafka| Python| Scala |GCP | Machine Learning| Azure| Generative AI | MLFlow

    📢📢 Generative AI Terminologies - Part 1 ➡️ Generative AI is revolutionising creativity and innovation. Imagine a tool that can write, design, or even craft entire experiences from just a few prompts. It's a game-changer for anyone in the creative space. ✅ In this series of articles, we'll explore some key terminologies in Generative AI to help you get familiar with this exciting technology. ✅ Types of Models 📌 Foundation Models 📌 Large Language Models (LLMs) 📌 Small Language Models (SLMs) 📌 Large Multimodal Models (LMMs) 📌 Vision Language Models (VLMs) 📌 Generative Image Models 📌 Text-to-Speech (TTS) 📌 Speech-to-Text (STT) ✅ Common LLM Terms 📌 Prompt 📌 Completion 📌 Inference 📌 Tokens 📌 Parameters 📌 Context Window 📌 Temperature 📌 Top N/P Sampling 📌 Hallucinations 📌 Bias and Toxicity ➡️ #download and #save. ✅ Lets together Demystify the Tech. ✅ Keep Learning!! Keep Growing!! ✅ Follow Sourav Banerjee if you wish to receive more such contents on Data Engineering, Databricks, Machine Learning, Cloud Engineering, Gen AI and MLOps. #generativeai #llm #genAI #transformers #demystifygenai

  • View organization page for Techelligence, Inc, graphic

    29,561 followers

    Very useful topics! #spark #learning #knowledge #interviews

    View profile for Karthik K., graphic

    𝐅𝐨𝐮𝐧𝐝𝐞𝐫 & 𝐂𝐄𝐎 @𝐒𝐞𝐞𝐤𝐡𝐨 𝐁𝐢𝐠𝐝𝐚𝐭𝐚 𝐈𝐧𝐬𝐭𝐢𝐭𝐮𝐭𝐞, 𝐁𝐢𝐠𝐝𝐚𝐭𝐚 𝐓𝐫𝐚𝐢𝐧𝐞𝐫

    𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠 𝐟𝐨𝐫 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰. 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐭𝐡𝐞 𝐑𝐞𝐩𝐚𝐫𝐭𝐢𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐂𝐨𝐚𝐥𝐞𝐬𝐜𝐞: Repartition and Coalesce are operations in Apache Spark that help manage the number of partitions in a DataFrame or RDD. "Follow Karthik K. Seekho Bigdata Institute for the latest updates and to learn more about data engineering topics!"

  • View organization page for Techelligence, Inc, graphic

    29,561 followers

    Databricks Vs Microsoft Fabric Thanks for sharing this Josue A. Bogran! #databricks #fabric

    View profile for Josue A. Bogran, graphic

    Architect @ Kythera Labs | Technical Advisor to SunnyData | Databricks Product Advisory Board Member & Databricks Beacon

    I recently wrote about Fabric vs Databricks from a neutral standpoint, but don't confuse my neutrality as saying they are equally as good. For most businesses and organizations, Databricks is the right choice. Here's why: 👉Cost With Databricks, you pay only for the compute that you use, when you use it, period. With Fabric, you are ALWAYS paying. It is the anti-cloud. Use it or lose it. You can borrow from the compute ahead and throttle yourself, but you can never get back what you paid for and didn't use. 👉Performance I never trust benchmarks as to which platform is faster than the other (read: Databricks vs Snowflake benchmarks), but benchmarks do help provide some directionally correct guidance. When Fabric is absent from performance benchmarks and there is little marketing as to its performance vs competitors, that is a big tell-tell. 👉Governance Unity Catalog is arguably one of the top 2 reasons why customers use Databricks. It makes data governance simple. Fantastic lineage capabilities, reporting through system tables, easy access control management, the list goes on. Meanwhile, Fabric users have the lighter version of Purview, which does offer some unique that UC does not have, but lacks many of them, and is more data observability than governance, an area that Databricks does a fair job in as well. 👉Orchestration Databricks Workflows work very well, are feature rich, and arguably are of the most mature Databricks offerings, second to UC. Solid at retaining job execution history, orchestrating pipelines efficiently, and allowing compute choice flexibility. Also job compute in Databricks is pretty darn cheap. Fabric offers Data Factory, which is okay for basic orchestration, but anything beyond basic orchestration, and it gets painful. 👉ETL Databricks doesn't offer good low-code solutions out of the box (an area Fabric does well in with Dataflows), but it is far more powerful when using code than Fabric can be with or without code. Databricks gives you plenty of methods to do ETL, both vendor and non-vendor specific. If no code/low code is your thing, Lakeflows (coming in the future), as well as 3rd party tools such as Prophecy can help bridge this gap. 👉Dashboards Power BI is the market leader, no doubt about that, and why Fabric bundled others services around it. I personally love using Power BI as well as Sigma for dashboards. That said, Databricks works extremely well with Power BI, even allowing you to create starter models straight from Databricks' UI. 👉Coding Experience The SQL Editor and Notebooks from Databricks offer great coding and data exploration experiences. Surprisingly, even leveraging charts in Databricks is easier than in Fabric's equivalents. 👉ML/AI Databricks is THE platform to emulate in this category. Ultimately: Fabric is good for small businesses that have a very limited tech skillset, but for most other businesses, Databricks is the top choice, while Fabric is in 4th place.

  • View organization page for Techelligence, Inc, graphic

    29,561 followers

    View organization page for Databricks, graphic

    743,947 followers

    We’re excited to announce the launch of Databricks Data Warehouse Brickbuilder Migration Solutions! Designed to enhance data warehousing capabilities, this expansion incorporates: - Databricks SQL to help businesses derive impactful insights - Delta Lake #UniForm to serve as the open storage layer - #UnityCatalog to provide security and governance. Learn more about the offerings with our new data warehouse migration partners, including Accenture, Avanade, Capgemini, Celebal Technologies, Cognizant, Deloitte, EPAM Systems, Impetus, Infosys, Koantek, Lovelytics, LTIMindtree, Nousot, Onix, Slalom, Tredence Inc., and Wipro. https://dbricks.co/3SZaQru

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  • Techelligence, Inc reposted this

    View profile for Derar Alhussein, graphic

    Sr. Data Engineer | O’Reilly Author | Udemy Instructor (50K Students) | Ex-Amazon | Databricks Beacon | 8x Databricks Certified

    Unity Catalog Best Practices 🚀 Unity Catalog is a centralized and open governance solution for all data and AI on the Databricks platform. The following document provides recommendations for using Unity Catalog to meet your data governance needs: https://lnkd.in/esc5XY_i In this article, you will learn: - Data governance and data isolation building blocks - Plan your data isolation model - Configure a Unity Catalog metastore - Configure external locations and storage credentials - Organize your data - Manage external locations, external tables, and external volumes - Configure access control - Manage cluster configurations - Audit access - Share data securely using Delta Sharing Happy Reading! #databricks #data #ai

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  • View organization page for Techelligence, Inc, graphic

    29,561 followers

    View profile for Prashant Kumar Pandey, graphic

    Retired at 46 from corporate job | Founder ScholarNest | Udemy Trainer | Author | Content Creator | Data and AI

    A list of 50 PySpark interview questions. Best part - Answers are included. Each question is answered very well and it gives you enough knowledge to answer a few other questions also. Credits Rahul Pupreja Keep learning and keep growing

  • Techelligence, Inc reposted this

    View profile for Sachin Chandrashekhar  🇮🇳, graphic

    Challenge > Learn AWS Data Engineering in 100 days! | 15K Family |3 million Views

    𝐋𝐞𝐭'𝐬 𝐛𝐞 𝐡𝐨𝐧𝐞𝐬𝐭 - 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚 𝐧𝐞𝐰 𝐬𝐤𝐢𝐥𝐥 𝐢𝐬𝐧'𝐭 𝐞𝐚𝐬𝐲 - 𝐞𝐬𝐩𝐞𝐜𝐢𝐚𝐥𝐥𝐲 #Apache 𝐒𝐩𝐚𝐫𝐤 𝐚𝐧𝐝 #aws 𝐂𝐥𝐨𝐮𝐝. There are so many moving parts that you got to know - as to how they fit together and how they orchestrate together. How do you then learn all of this? By being consistent By being persistent By being resilient Attached are some handy notes on #spark for you. P.S ✅Version 3 of 𝐬𝐜𝐞𝐧𝐚𝐫𝐢𝐨 𝐛𝐚𝐬𝐞𝐝 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 𝐑𝐞𝐚𝐥-world AWS Data Engineering ( RADE™) program 𝐰𝐢𝐭𝐡 80 𝐚𝐦𝐚𝐳𝐢𝐧𝐠 𝐩𝐞𝐨𝐩𝐥𝐞 started on July 28th; 4 𝐒𝐎𝐋𝐈𝐃 𝐇𝐀𝐍𝐃𝐒 𝐎𝐍 𝐒𝐄𝐒𝐒𝐈𝐎𝐍s 𝐀𝐑𝐄 𝐃𝐎𝐍𝐄! ✅𝐈𝐟 𝐲𝐨𝐮 𝐚𝐫𝐞 𝐚𝐜𝐭𝐢𝐨𝐧-𝐨𝐫𝐢𝐞𝐧𝐭𝐞𝐝 and want to get in the next batch, fill the form below to be get invited for the webinar for RADE™ program V4 Click on "𝐕𝐢𝐬𝐢𝐭 𝐦𝐲 𝐰𝐞𝐛𝐬𝐢𝐭𝐞" on my profile. 𝐔𝐒𝐏: 𝐑𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐬𝐜𝐞𝐧𝐚𝐫𝐢𝐨 𝐛𝐚𝐬𝐞𝐝 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐝 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 program ! doc credit -Myself :) #aws #dataengineering

  • Techelligence, Inc reposted this

    View profile for Abhinav Singh, graphic

    Data Engineer @AHEAD | Spark, Azure, Python, Databricks, Snowflake, SQL | Building robust, scalable data solutions to fuel business insights

    5 frequently Asked SQL Interview Questions with Answers in Data Engineering interviews: 𝐃𝐢𝐟𝐟𝐢𝐜𝐮𝐥𝐭𝐲 - 𝐌𝐞𝐝𝐢𝐮𝐦 ⚫️Find the Top 3 Employees with the Highest Total Sales in Each Region   Schema : Using Employees (EmployeeID, Name, RegionID) and Sales (SaleID, EmployeeID, Amount) WITH RankedSales AS ( SELECT e.EmployeeID, e.Name, e.RegionID, SUM(s.Amount) AS TotalSales, RANK() OVER (PARTITION BY e.RegionID ORDER BY SUM(s.Amount) DESC) AS SalesRank FROM Employees e JOIN Sales s ON e.EmployeeID = s.EmployeeID GROUP BY e.EmployeeID, e.Name, e.RegionID ) SELECT EmployeeID, Name, RegionID, TotalSales FROM RankedSales WHERE SalesRank <= 3; ⚫️Identify Products with Sales Increasing for Three Consecutive Months  Schema :  Sales (ProductID, SaleDate, Quantity). WITH MonthlySales AS ( SELECT ProductID, DATE_TRUNC('month', SaleDate) AS Month, SUM(Quantity) AS MonthlyQuantity FROM Sales GROUP BY ProductID, DATE_TRUNC('month', SaleDate) ), SalesGrowth AS ( SELECT ProductID, Month, MonthlyQuantity, LAG(MonthlyQuantity, 1) OVER (PARTITION BY ProductID ORDER BY Month) AS PrevMonth1, LAG(MonthlyQuantity, 2) OVER (PARTITION BY ProductID ORDER BY Month) AS PrevMonth2 FROM MonthlySales ) SELECT ProductID, Month, MonthlyQuantity FROM SalesGrowth WHERE MonthlyQuantity > PrevMonth1 AND PrevMonth1 > PrevMonth2; ⚫️List Customers Who Placed Orders in Consecutive Months Schema : Orders (OrderID, CustomerID, OrderDate) WITH MonthlyOrders AS ( SELECT CustomerID, DATE_TRUNC('month', OrderDate) AS OrderMonth FROM Orders GROUP BY CustomerID, DATE_TRUNC('month', OrderDate) ), ConsecutiveMonths AS ( SELECT CustomerID, OrderMonth, LAG(OrderMonth, 1) OVER (PARTITION BY CustomerID ORDER BY OrderMonth) AS PrevMonth FROM MonthlyOrders ) SELECT DISTINCT CustomerID FROM ConsecutiveMonths WHERE OrderMonth = PrevMonth INTERVAL '1 month'; ⚫️Find the Second Highest Salary in Each Department   Schema: Employees (EmployeeID, Name, DepartmentID, Salary)   WITH RankedSalaries AS (     SELECT DepartmentID,         Salary,         DENSE_RANK() OVER (PARTITION BY DepartmentID ORDER BY Salary DESC) AS Rank     FROM Employees   )   SELECT DepartmentID, Salary   FROM RankedSalaries   WHERE Rank = 2; ⚫️Calculate the Moving Average of Sales for Each Product Over the Last 3 Months  Schema : Given Sales (SaleID, ProductID, SaleDate, Amount) SELECT ProductID, SaleDate, Amount, AVG(Amount) OVER (PARTITION BY ProductID ORDER BY SaleDate ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS MovingAvg FROM Sales; ♻️ I hope you found this useful! If you did, please repost it. 👋🏽 Follow me for more about the Data career.

  • Techelligence, Inc reposted this

    View profile for Deep Contractor, graphic

    Databricks RSA @ Celebal | Kaggle Grandmaster | Featured in Analytics India Magazine | Azure & AWS | ML & MLOps | Databricks Certified X2 | Microsoft Workshop Instructor

    Databricks and JetBrains have just announced a new integration between PyCharm, the powerful Python IDE and Databricks platform. This will help you - ▪️Connect to your cluster using PyCharm. ▪️Run Python scripts on remote cluster. ▪️Run notebooks are workflows. ▪️Sync project files with DB workspace. A data professional can now use PyCharm to implement software development best practices, which are essential for large codebases, such as source code control, modular code layouts, testing, and more.

    Announcing the PyCharm Integration with Databricks

    Announcing the PyCharm Integration with Databricks

    databricks.com

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