#dataengineering

[pilog-group]

How Dr. Imad Syed Transformed PiLog Group into a Digital Transformation Leader?

The digital age demands leaders who don’t just adapt but drive transformation. One such visionary is Dr. Imad Syed, who recently shared his incredible journey and PiLog Group’s path to success in an exclusive interview on Times Now.

In this inspiring conversation, Dr. Syed reflects on the milestones, challenges, and innovative strategies that have positioned PiLog Group as a global leader in data management and digital transformation.

The Journey of a Visionary:

From humble beginnings to spearheading PiLog’s global expansion, Dr. Syed’s story is a testament to resilience and innovation. His leadership has not only redefined PiLog but has also influenced industries worldwide, especially in domains like data governance, SaaS solutions, and AI-driven analytics.

PiLog’s Success: A Benchmark in Digital Transformation:

Under Dr. Syed’s guidance, PiLog has become synonymous with pioneering Lean Data Governance SaaS solutions. Their focus on data integrity and process automation has helped businesses achieve operational excellence. PiLog’s services are trusted by industries such as oil and gas, manufacturing, energy, utilities & nuclear and many more.

Key Insights from the Interview:

In the interview, Dr. Syed touches upon:

The importance of data governance in digital transformation.

How PiLog’s solutions empower organizations to streamline operations.

His philosophy of continuous learning and innovation.

A Must-Watch for Industry Leaders:

If you’re a business leader or tech enthusiast, this interview is packed with actionable insights that can transform your understanding of digital innovation.

👉 Watch the full interview here:

The Global Impact of PiLog Group:

PiLog’s success story resonates globally, serving clients across Africa, the USA, EU, Gulf countries, and beyond. Their ability to adapt and innovate makes them a case study in leveraging digital transformation for competitive advantage.

Join the Conversation:

What’s your take on the future of data governance and digital transformation? Share your thoughts and experiences in the comments below.

[ai-resume-builder]

Data Professionals: Want to Stand Out?

If you're a Data Engineer, Data Scientist, or Data Analyst, having a strong portfolio can be a game-changer.

Our latest blog dives into why portfolios matter, what to include, and how to build one that shows off your skills and projects. From data pipelines to machine learning models and interactive dashboards, let your work speak for itself!

[wuedk]

🚀 𝐉𝐨𝐢𝐧 𝐃𝐚𝐭𝐚𝐏𝐡𝐢'𝐬 𝐇𝐚𝐜𝐤-𝐈𝐓-𝐎𝐔𝐓 𝐇𝐢𝐫𝐢𝐧𝐠 𝐇𝐚𝐜𝐤𝐚𝐭𝐡𝐨𝐧!🚀

𝐖𝐡𝐲 𝐏𝐚𝐫𝐭𝐢𝐜𝐢𝐩𝐚𝐭𝐞? 🌟 Showcase your skills in data engineering, data modeling, and advanced analytics. 💡 Innovate to transform retail services and enhance customer experiences.

📌𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐍𝐨𝐰: https://whereuelevate.com/drills/dataphi-hack-it-out?w_ref=CWWXX9

🏆 𝐏𝐫𝐢𝐳𝐞 𝐌𝐨𝐧𝐞𝐲: Winner 1: INR 50,000 (Joining Bonus) + Job at DataPhi Winners 2-5: Job at DataPhi

🔍 𝐒𝐤𝐢𝐥𝐥𝐬 𝐖𝐞'𝐫𝐞 𝐋𝐨𝐨𝐤𝐢𝐧𝐠 𝐅𝐨𝐫: 🐍 Python,💾 MS Azure Data Factory / SSIS / AWS Glue,🔧 PySpark Coding,📊 SQL DB,☁️ Databricks Azure Functions,🖥️ MS Azure,🌐 AWS Engineering

👥 𝐏𝐨𝐬𝐢𝐭𝐢𝐨𝐧𝐬 𝐀𝐯𝐚𝐢𝐥𝐚𝐛𝐥𝐞: Senior Consultant (3-5 years) Principal Consultant (5-8 years) Lead Consultant (8+ years)

📍 𝐋𝐨𝐜𝐚𝐭𝐢𝐨𝐧: 𝐏𝐮𝐧𝐞 💼 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: 𝟑-𝟏𝟎 𝐘𝐞𝐚𝐫𝐬 💸 𝐁𝐮𝐝𝐠𝐞𝐭: ₹𝟏𝟒 𝐋𝐏𝐀 - ₹𝟑𝟐 𝐋𝐏𝐀

ℹ 𝐅𝐨𝐫 𝐌𝐨𝐫𝐞 𝐔𝐩𝐝𝐚𝐭𝐞𝐬: https://chat.whatsapp.com/Ga1Lc94BXFrD2WrJNWpqIa

Register now and be a part of the data revolution! For more details, visit DataPhi.

[jinactusconsulting]

What sets Konnect Insights apart from other data orchestration and analysis tools available in the market for improving customer experiences in the aviation industry?

I can highlight some general factors that may set Konnect Insights apart from other data orchestration and analysis tools available in the market for improving customer experiences in the aviation industry. Keep in mind that the competitive landscape and product offerings may have evolved since my last knowledge update. Here are some potential differentiators:

Aviation Industry Expertise: Konnect Insights may offer specialized features and expertise tailored to the unique needs and challenges of the aviation industry, including airports, airlines, and related businesses.

Multi-Channel Data Integration: Konnect Insights may excel in its ability to integrate data from a wide range of sources, including social media, online platforms, offline locations within airports, and more. This comprehensive data collection can provide a holistic view of the customer journey.

Real-Time Monitoring: The platform may provide real-time monitoring and alerting capabilities, allowing airports to respond swiftly to emerging issues or trends and enhance customer satisfaction.

Customization: Konnect Insights may offer extensive customization options, allowing airports to tailor the solution to their specific needs, adapt to unique workflows, and focus on the most relevant KPIs.

Actionable Insights: The platform may be designed to provide actionable insights and recommendations, guiding airports on concrete steps to improve the customer experience and operational efficiency.

Competitor Benchmarking: Konnect Insights may offer benchmarking capabilities that allow airports to compare their performance to industry peers or competitors, helping them identify areas for differentiation.

Security and Compliance: Given the sensitive nature of data in the aviation industry, Konnect Insights may include robust security features and compliance measures to ensure data protection and adherence to industry regulations.

Scalability: The platform may be designed to scale effectively to accommodate the data needs of large and busy airports, ensuring it can handle high volumes of data and interactions.

Customer Support and Training: Konnect Insights may offer strong customer support, training, and consulting services to help airports maximize the value of the platform and implement best practices for customer experience improvement.

Integration Capabilities: It may provide seamless integration with existing airport systems, such as CRM, ERP, and database systems, to ensure data interoperability and process efficiency.

Historical Analysis: The platform may enable airports to conduct historical analysis to track the impact of improvements and initiatives over time, helping measure progress and refine strategies.

User-Friendly Interface: Konnect Insights may prioritize a user-friendly and intuitive interface, making it accessible to a wide range of airport staff without requiring extensive technical expertise.

It's important for airports and organizations in the aviation industry to thoroughly evaluate their specific needs and conduct a comparative analysis of available solutions to determine which one aligns best with their goals and requirements. Additionally, staying updated with the latest developments and customer feedback regarding Konnect Insights and other similar tools can provide valuable insights when making a decision.

[thebattlefordatasupremacy]

Data Engineer vs. Data Scientist The Battle for Data Supremacy

In the rapidly evolving landscape of technology, two professions have emerged as the architects of the data-driven world: Data Engineers and Data Scientists. In this comparative study, we will dive deep into the worlds of these two roles, exploring their unique responsibilities, salary prospects, and essential skills that make them indispensable in the realm of Big Data and Artificial Intelligence.

The world of data is boundless, and the roles of Data Engineers and Data Scientists are indispensable in harnessing its true potential. Whether you are a visionary Data Engineer or a curious Data Scientist, your journey into the realm of Big Data and AI is filled with infinite possibilities. Enroll in the School of Core AI’s Data Science course to day and embrace the future of technology with open arms.

[arkatiss]

Arkatiss LLP is a digital transformation solutions company, helping organizations in business process reengineering, data engineering and information sharing solutions to accelerate automation as a long-term goal for better ROI

[datavalleyai]

Most Popular Upskilled Courses & upskill your Knowledge...more information visit :- https://datavalley.ai/

[excelworld]

[rtc-tek]

Agile data systems enable businesses to innovate and scale with confidence. At #RoundTheClockTechnologies, data engineering services are designed to provide clean, integrated, and business-aligned datasets that fuel innovation across every department. From setting up reliable data lakes to configuring BI-friendly data marts, our solutions bridge the gap between raw inputs and strategic outcomes.

We automate complex transformations, eliminate data duplication, and ensure that every pipeline is optimized for speed and accuracy. Leveraging platforms like AWS, Snowflake, and Azure, we create secure and high-performing data environments tailored to business needs. Whether supporting real-time analytics or feeding predictive models, our goal is to help organizations unlock the full value of their data assets—efficiently, consistently, and securely.

Learn more about our data engineering services at https://rtctek.com/data-engineering-services/

[hubertdudek]

Databricks: what’s new in April 2025? Updates & Features Explained! #databricks Databricks, What’s New in Databricks? April 2025 Updates & Features Explained! 📌 Key Highlights for This Month: - *00:04* PowerBI task - Refresh PowerBI from Databricks - *01:36* SQL task values - Pass SELECT result to workflow - *05:38* Cost-optimized jobs - Serverless standard mode - *06:34* Google Sheets - Query Databricks - *07:48* Git for dashboards - *08:38* Genie sampling - Genie can read data - *11:22* UC functions with PyPl libraries - *12:22* Anomaly detection - *15:02* PII scanner - Data classification - *16:13* Turn off Hive metastore - *17:17* AI builder - Extract data and more - *21:12* AI query with schema - *22:41* PyDABS - *23:28* ALTER statement - *24:03* TEMP VIEWS in DLT - *24:18* Apps on behalf of the user ============================= 📚 *Notebooks from the video:* 🔗 [GitHub Repository](https://ift.tt/S13qG0b) 🔔𝐃𝐨𝐧'𝐭 𝐟𝐨𝐫𝐠𝐞𝐭 𝐭𝐨 𝐬𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐦𝐲 𝐜𝐡𝐚𝐧𝐧𝐞𝐥 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐮𝐩𝐝𝐚𝐭𝐞𝐬. https://www.youtube.com/@hubert_dudek/?sub_confirmation=1 🔗 Support Me Here! ☕Buy me a coffee: https://ift.tt/9qIpuET ✨ Explore Databricks AI insights and workflows—read more: https://ift.tt/1djZykN ============================= 🎬Suggested videos for you: ▶️ [What’s new in January 2025](https://www.youtube.com/watch?v=JJiwSplZmfk) ▶️ [What’s new in February 2025](https://www.youtube.com/watch?v=tuKI0sBNbmg) ▶️ [What’s new in March 2025](https://youtu.be/hJD7KoNq-uE) ============================= 📚 **New Articles for Further Reading:** - ��� *More on Databricks into Google Sheets:* 🔗 [Read the full article](https://ift.tt/3cfjJLy) - 📝 *More on Anomaly Detection & Data Freshness:* 🔗 [Read the full article](https://ift.tt/5RB4bWM) - 📝 *More on Goodbye to Hive Metastore:* 🔗 [Read the full article](https://ift.tt/lxjpoRS) - 📝 *More on Databricks Refresh PowerBI Semantic Model:* 🔗 [Read the full article](https://ift.tt/8JAfSvZ) - 📝 *More on ResponseFormat in AI Batch Inference:* 🔗 [Read the full article](https://ift.tt/B07yqRT) ============================= 🔎 Related Phrases: #databricks #bigdata #dataengineering #machinelearning #sql #cloudcomputing #dataanalytics #ai #azure #googlecloud #aws #etl #python #data #database #datawarehouse via Hubert Dudek https://www.youtube.com/channel/UCR99H9eib5MOHEhapg4kkaQ April 22, 2025 at 02:17AM

[tudipblog]

Medallion Architecture: A Scalable Framework for Modern Data Management

In the current big data era, companies must effectively manage data to make data-driven decisions. One such well-known data management architecture is the Medallion Architecture. This architecture offers a structured, scalable, modular approach to building data pipelines, ensuring data quality, and optimizing data operations.

What is Medallion Architecture?

Medallion Architecture is a system for managing and organizing data in stages. Each stage, or “medallion,” improves the quality and usefulness of the data, step by step. The main goal is to transform raw data into meaningful data that is ready for the analysis team.

The Three Layers of Medallion Architecture:

Bronze Layer (Raw Data):This layer stores all raw data exactly as it comes in without any changes or cleaning, preserving a copy of the original data for fixing errors or reprocessing when needed. Example: Logs from a website, sensor data, or files uploaded by users.

Silver Layer (Cleaned and Transformed Data):The Silver Layer involves cleaning, organizing, and validating data by fixing errors such as duplicates or missing values, ensuring the data is consistent and reliable for analysis, such as removing duplicate customer records or standardizing dates in a database Example: Removing duplicate customer records or standardizing dates in a database.

Gold Layer (Business-Ready Data):The Gold Layer contains final, polished data optimized for reports, dashboards, and decision-making, providing businesses with exactly the information they need to make informed decisions Example: A table showing the total monthly sales for each region

Advantages:

Improved Data Quality: Incremental layers progressively refine data quality from raw to business-ready datasets

Scalability: Each layer can be scaled independently based on specific business requirements

Security: If you have a large team to handle, you can separate them by their level

Modularity: The layered approach separates responsibilities, simplifying management and debugging

Traceability: Raw data preserved in the Bronze layer ensures traceability and allows reprocessing when issues arise in downstream layers

Adaptability: The architecture supports diverse data sources and formats, making it suitable for various business needs

Challenges:

Takes Time: Processing through multiple layers can delay results

Storage Costs: Storing raw and processed data requires more space

Requires Skills: Implementing this architecture requires skilled data engineers familiar with ETL/ELT tools, cloud platforms, and distributed systems

Best Practices for Medallion Architecture:

Automate ETL/ELT Processes: Use orchestration tools like Apache Airflow or AWS Step Functions to automate workflows between layers

Enforce Data Quality at Each Layer: Validate schemas, apply deduplication rules, and ensure data consistency as it transitions through layers

Monitor and Optimize Performance: Use monitoring tools to track pipeline performance and optimize transformations for scalability

Leverage Modern Tools: Adopt cloud-native technologies like Databricks, Delta Lake, or Snowflake to simplify the implementation

Plan for Governance: Implement robust data governance policies, including access control, data cataloging, and audit trails

Conclusion

Medallion Architecture is a robust framework for building reliable, scalable, and modular data pipelines. Its layered approach allows businesses to extract maximum value from their data by ensuring quality and consistency at every stage. While it comes with its challenges, the benefits of adopting Medallion Architecture often outweigh the drawbacks, making it a cornerstone for modern data engineering practices.

To learn more about this blog, please click on the link below: https://tudip.com/blog-post/medallion-architecture/.

[fraoula1]

𝐇𝐨𝐰 𝐀𝐢𝐫𝐛𝐧𝐛 𝐀𝐧𝐚𝐥𝐲𝐳𝐞𝐬 1 𝐁𝐢𝐥𝐥𝐢𝐨𝐧+ 𝐃𝐚𝐭𝐚 𝐏𝐨𝐢𝐧𝐭𝐬 𝐃𝐀𝐈𝐋𝐘 (𝐓𝐡𝐞𝐢𝐫 𝐅𝐮𝐥𝐥 𝐃𝐚𝐭𝐚 𝐒𝐭𝐚𝐜𝐤)

Airbnb processes over 1 billion data points every single day. From real-time pricing to fraud detection, this video breaks down their end-to-end data stack: storage, processing, analytics, and machine learning workflows.

Whether you're a data engineer, analyst, or CTO, this is your blueprint for scalable analytics at a global scale.

Watch https://youtu.be/Chg3sCd8Zns

[rtc-tek]

Data is at the core of digital transformation, driving innovation and business agility. Future-ready data engineering strategies leverage automation, AI, and cloud technologies to streamline workflows, enhance analytics capabilities, and unlock new revenue opportunities.

A structured approach ensures seamless integration, secure data governance, and high-performance processing pipelines. Scalable architectures future-proof operations, allowing businesses to adapt to evolving market demands.

With #RoundTheClockTechnologies, enterprises gain a strategic partner in navigating the complexities of modern data ecosystems, ensuring sustained growth and competitive advantage in an increasingly data-driven world.

Learn more about our data engineering services at https://rtctek.com/data-engineering-services/

[tartlabs]

How Data Engineering Fuels Your Digital World!

Ever stopped to think how Spotify knows your taste in music? Or how online stores seem to know exactly what you need before you do? It’s all thanks to Data Engineering!

Data Engineers work behind the scenes to collect, process, and manage data so businesses can make smarter decisions. Without them, AI and analytics wouldn’t work! That’s why top data engineering solutions are in huge demand today.

How Data Engineering Works 🔹 Data Ingestion – Gathering data from multiple sources 🔹 Data Storage – Organizing everything in warehouses & lakes 🔹 Data Pipelines – Automating workflows for smooth processing 🔹 Cloud Integration – Scaling businesses effortlessly

Companies worldwide are turning to top Data Engineering services in Coimbatore, like Tart Labs, to build smart, efficient data systems.

Want to see how it all works? Check out our blog at Tart Labs!

📖 Read here: Data Engineering a Complete Guide