ProjectPro

JUNE 6, 2025

Learn all about Azure ETL Tools in minutes with this quick guide, showcasing the top 7 Azure tools with their key features, pricing, and pros/cons for your data processing needs. Many are turning to Azure ETL tools for their simplicity and efficiency, offering a seamless experience for easy data extraction, transformation, and loading.

ETL Tools

ProjectPro

JUNE 6, 2025

This blog is your ultimate gateway to transforming yourself into a skilled and successful Big Data Developer, where your analytical skills will refine raw data into strategic gems. So, get ready to turn the turbulent sea of 'data chaos' into 'data artistry.' What industry is big data developer in?

Big Data

ProjectPro

JUNE 6, 2025

Think of the data integration process as building a giant library where all your data's scattered notebooks are organized into chapters. You define clear paths for data to flow, from extraction (gathering structured/unstructured data from different systems) to transformation (cleaning the raw data, processing the data, etc.)

Data Integration

ProjectPro

JUNE 6, 2025

According to I DC’s Data Age Report , the digital universe is likely to reach 175 zettabytes by 2025, showing the exponential growth of data with the increasing complexity of analysis. It supports flexible instance and storage scaling to accommodate varying workloads.

AWS

ProjectPro

JUNE 6, 2025

Elevate your data processing skills with Amazon Managed Streaming for Apache Kafka, making real-time data streaming a breeze. Deeply Integrated: Seamlessly integrate AWS Kafka with various AWS services, including analytics, storage, and machine learning offerings. billion in 2023 at a CAGR of 26.9%.

Kafka

ProjectPro

JUNE 6, 2025

A data lake retains all data, including data currently in use, data that may be used and even data that may never actually be used, but there is some assumption that it may be of some help in the future. In Data lakes the schema is applied by the query and they do not have a rigorous schema like data warehouses.

Data Lake

ProjectPro

JUNE 6, 2025

AWS Glue is a widely-used serverless data integration service that uses automated extract, transform, and load ( ETL ) methods to prepare data for analysis. It offers a simple and efficient solution for data processing in organizations. It was responsible for extracting data and categorizing it.

AWS

ProjectPro

JUNE 6, 2025

Skills Developed : Real-time data processing with Kafka Building anomaly detection workflows Real-time visualization with Grafana 7) Weather Pattern Prediction Industries like agriculture, logistics, and disaster management need accurate weather predictions to reduce risks and improve operational planning.

Data Engineering

ProjectPro

JUNE 6, 2025

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis.

Hadoop

ProjectPro

JUNE 6, 2025

With the proliferation of data sources, IoT devices, and edge nodes, almost 2.5 quintillion bytes of data is produced daily. This data is distributed across many platforms, including cloud databases, websites, CRM tools, social media channels, email marketing, etc.

Data Engineering

Teradata

JUNE 30, 2025

AI data architecture is the integrated framework that governs how data is ingested, processed, stored, and managed to support artificial intelligence applications. Key components of AI data architecture An effective AI data architecture includes: 1.

Data Architecture

ProjectPro

JUNE 6, 2025

According to Wasabi's 2023 Cloud Storage Index Executive Summary Report, Nearly 90% of respondents stated they had switched from on-premises to cloud storage solutions due to better system resilience, durability, and scalability. Storage Capacity : The pricing for Azure Blob Storage is based on the data stored in your account.

Cloud Storage

ProjectPro

JUNE 6, 2025

When combined with the distributed computing framework of Hadoop, businesses can leverage the scalability and parallel processing capabilities of Hadoop to efficiently manage and process their big data. Both structured and unstructured data in distributed file systems. Faster processing time for large data sets.

Hadoop

ProjectPro

JUNE 6, 2025

Since then, it has been used by companies operating in various industries to manage big data archives, providing a platform for them to build their own custom software services to store and process data. Real-time data streaming also helps to reduce the amount of data storage solutions needed.

Kafka

ProjectPro

JUNE 6, 2025

Focussed on designing, building, and maintaining large-scale data processing systems. Extract, transform, and load data into a target system. Works on data storage and retrieval, data processing, and data visualization. Works with databases, ETL tools, and scripting languages.

ETL Tools

ProjectPro

JUNE 6, 2025

Features of GCP GCP offers services, including Machine learning analytics Application modernization Security Business Collaboration Productivity Management Cloud app development Data Storage, and management AWS - Amazon Web Services - An Overview Amazon Web Services is the largest cloud provider, developed and maintained by Amazon.

AWS

ProjectPro

JUNE 6, 2025

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering

ProjectPro

JUNE 6, 2025

GCP Data Engineer Certification The Google Cloud Certified Professional Data Engineer certification is ideal for data professionals whose jobs generally involve data governance, data handling, data processing, and performing a lot of feature engineering on data to prepare it for modeling.

Certification

ProjectPro

JUNE 6, 2025

Big data is often characterized by the seven V's: Volume , Variety , Velocity, Variability, Veracity, Visualization, and Value of data. Big data engineers leverage big data tools and technologies to process and engineer massive data sets or data stored in data storage systems like databases and data lakes.

Big Data

ProjectPro

JUNE 6, 2025

One of the leading cloud service providers, Amazon Web Services (AWS ), offers powerful tools and services that can propel your data analysis endeavors to new heights. With AWS, you gain access to scalable infrastructure, robust data storage, and cutting-edge analytics capabilities.

AWS

ProjectPro

JUNE 6, 2025

Azure Stack Familiarize yourself with core Microsoft Azure data services such as Azure Data Lake, Azure Synapse, Azure Data Factory , Azure Cosmos DB, etc. According to the Microsoft Study Guide, you must focus on preparing the following topics: Describe core data concepts. Describe ways to represent data.

Certification

ProjectPro

JUNE 6, 2025

You can pick any of these cloud computing project ideas to develop and improve your skills in the field of cloud computing along with other big data technologies. The project emphasizes end-to-end testing of AWS Lambda functions and integration with DynamoDB for data storage.

Cloud Computing

ProjectPro

JUNE 6, 2025

Data rights: People are entitled to see, amend, remove, and limit how their data is processed. Data Processing Transparency: People need to know how their data is going to be used. Security: To safeguard personal information, data scientists need to put in place the proper security measures.

Data Science

ProjectPro

JUNE 6, 2025

Starting with setting up an Azure Virtual Machine, you'll install necessary big data tools and configure Flume agents for log data ingestion. Utilizing Spark for data processing and Hive for querying, you'll develop a comprehensive understanding of real-time log analysis in a cloud environment.​

Project

ProjectPro

JUNE 6, 2025

These platforms provide scalable infrastructure and services for machine learning, such as distributed training, model serving, and data processing. An example of scalability in machine learning can be seen in the field of natural language processing ( NLP ).

Machine Learning

ProjectPro

JUNE 6, 2025

It focuses on the following key areas- Core Data Concepts- Understanding the basics of data concepts, such as relational and non-relational data, structured and unstructured data, data ingestion, data processing, and data visualization.

Certification

ProjectPro

JUNE 6, 2025

Using data analysis , you can build an advanced demand forecasting system that minimizes stockouts and overstock situations. Weather Data: Seasonal demand fluctuations (NOAA Climate Data). Social Media Trends: Consumer sentiment analysis (Twitter , Reddit APIs).

Data Science

Data Engineering Podcast

DECEMBER 31, 2018

To help other people find the show please leave a review on iTunes , or Google Play Music , tell your friends and co-workers, and share it on social media. To help other people find the show please leave a review on iTunes , or Google Play Music , tell your friends and co-workers, and share it on social media.

Lambda Architecture

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. This information is gathered from a variety of sources, including sensor readings, social media engagements, and client transactions. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly.

Data Process

Knowledge Hut

APRIL 25, 2024

Big data is a term that refers to the massive volume of data that organizations generate every day. In the past, this data was too large and complex for traditional data processing tools to handle. There are a variety of big data processing technologies available, including Apache Hadoop, Apache Spark, and MongoDB.

Big Data

Striim

SEPTEMBER 11, 2024

Striim, for instance, facilitates the seamless integration of real-time streaming data from various sources, ensuring that it is continuously captured and delivered to big data storage targets. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline

AltexSoft

JULY 18, 2023

It allows data scientists to analyze large datasets and interactively run jobs on them from the R shell. Big data processing. For instance, social media platforms may use GraphX to analyze user connections and suggest potential friends. Here are some of the possible use cases.

Big Data

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. Source Code: Finnhub API with Kafka for Real-Time Financial Market Data Pipeline 3.

Data Engineering

Towards Data Science

OCTOBER 7, 2023

Automate engineering and data processes By automating repetitive or mundane aspects of coding and data engineering, generative AI is streamlining workflows and driving productivity for software and data engineers alike. Even at OpenAI itself, LLMs are used to support DevOps and internal functions.

Unstructured Data

Knowledge Hut

APRIL 23, 2024

The history of big data takes people on an astonishing journey of big data evolution, tracing the timeline of big data. The Emergence of Data Storage and Processing Technologies A data storage facility first appeared in the form of punch cards, developed by Basile Bouchon to facilitate pattern printing on textiles in looms.

Big Data

Towards Data Science

FEBRUARY 15, 2023

Concepts, theory, and functionalities of this modern data storage framework Photo by Nick Fewings on Unsplash Introduction I think it’s now perfectly clear to everybody the value data can have. To use a hyped example, models like ChatGPT could only be built on a huge mountain of data, produced and collected over years.

Data Lake

AltexSoft

MAY 12, 2023

Unlike structured data, which is organized into neat rows and columns within a database, unstructured data is an unsorted and vast information collection. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc. Social media posts.

Unstructured Data