ProjectPro

JUNE 6, 2025

Why Learn Cloud Computing Skills? The job market in cloud computing is growing every day at a rapid pace. A quick search on Linkedin shows there are over 30000 freshers jobs in Cloud Computing and over 60000 senior-level cloud computing job roles. What is Cloud Computing? Thus came in the picture, Cloud Computing.

Cloud Computing 53

Cloud Computing Cloud Amazon Web Services AWS 53

ProjectPro

JUNE 6, 2025

Data is often referred to as the new oil, and just like oil requires refining to become useful fuel, data also needs a similar transformation to unlock its true value. This transformation is where data warehousing tools come into play, acting as the refining process for your data. Practice makes a man perfect!

Data Storage 58

Data Storage PostgreSQL Data Warehouse AWS 58

ProjectPro

JUNE 6, 2025

For e.g., Finaccel, a leading tech company in Indonesia, leverages AWS Glue to easily load, process, and transform their enterprise data for further processing. Another leading European company, Claranet, has adopted Glue to migrate their data load from their existing on-premise solution to the cloud. How Does AWS Glue Work?

AWS 66

AWS Scala Metadata Data Lake 66

Snowflake

NOVEMBER 11, 2024

At BUILD 2024, we announced several enhancements and innovations designed to help you build and manage your data architecture on your terms. This reduces the overall complexity of getting streaming data ready to use: Simply create external access integration with your existing Kafka solution. Here’s a closer look.

Data Architecture 105

Data Architecture Architecture Data Lake Kafka 105

ProjectPro

JUNE 6, 2025

Amazon offers top database services, such as RDS, Aurora , Redshift , DynamoDB, etc., which allow users to create relational, graph, wide-column, and other use-case-specific data models. These databases are completely managed by AWS, relieving users of time-consuming activities like server provisioning, patching, and backup.

Amazon Web Services 40

Amazon Web Services NoSQL Relational Database AWS 40

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

JUNE 6, 2025

Skills of a Data Engineer Apart from the existing skills of an ETL developer, one must acquire the following additional skills to become a data engineer. Cloud Computing Every business will eventually need to move its data-related activities to the cloud.

Data Engineer 59

Data Engineer Data Engineering Engineering ETL Tools 59

ProjectPro

JUNE 6, 2025

Any inconsistencies found in the data are removed, and all gaps that can be filled are filled to ensure that the data maintains integrity. Data Warehouse Layer: Once the data is transformed into the required format, it is saved into a central repository. Is Hadoop a data lake or data warehouse?

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

JUNE 6, 2025

Furthermore, you will find a few sections on data engineer interview questions commonly asked in various companies leveraging the power of big data and data engineering. Differentiate between relational and non-relational database management systems. SQL works on data arranged in a predefined schema.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

Decide the process of Data Extraction and transformation, either ELT or ETL (Our Next Blog) Transforming and cleaning data to improve data reliability and usage ability for other teams from Data Science or Data Analysis. Dealing With different data types like structured, semi-structured, and unstructured data.

Data Science 40

Data Science Data Engineering Data Engineer Engineering 40

phData: Data Engineering

NOVEMBER 8, 2024

Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data. Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

ProjectPro

JUNE 6, 2025

Client Applications Amazon Redshift can integrate with different ETL tools, BI tools, data mining , and analytics tools. Clusters The basic unit in the AWS cloud architecture is the Amazon Redshift cluster. Databases Amazon Redshift database is a relational database management system compatible with other RDMS applications.

Data Pipeline 64

Data Pipeline AWS Project Building 64

ProjectPro

JUNE 6, 2025

A primary key is a column or set of columns in a relational database management system table that uniquely identifies each record. To avoid null values and duplicate entries, the primary key constraint is applied to the column data. What is a hierarchical database management system (DBMS)? What is a surrogate key?

Data Warehouse 53

Data Warehouse NoSQL PostgreSQL Relational Database 53

ProjectPro

JUNE 6, 2025

Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics. Data Migration - This is another key use case where ETL processes can be used to migrate data from an on-premises system to the cloud.

BI 45

BI ETL Tools Retail Healthcare 45

ProjectPro

JUNE 6, 2025

Here are several examples: Security architects design and implement security practices to ensure data confidentiality, integrity, and availability. Cloud Architect stays up-to-date with data regulations, monitors data accessibility, and expands the cloud infrastructure as needed.

Data Architect 40

Data Architect Data Mining Programming Language Java 40

ProjectPro

JUNE 6, 2025

They include relational databases like Amazon RDS for MySQL, PostgreSQL, and Oracle and NoSQL databases like Amazon DynamoDB. Types of AWS Databases AWS provides various database services, such as Relational Databases Non-Relational or NoSQL Databases Other Cloud Databases ( In-memory and Graph Databases).

AWS 40

AWS Database Amazon Web Services MySQL 40

ProjectPro

JUNE 6, 2025

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 40

Big Data Hadoop Relational Database AWS 40

ProjectPro

JUNE 6, 2025

Zero ETL helps mitigate these costs by reducing duplicate data storage and minimizing the need for constant monitoring and testing, thus lowering overall maintenance expenses. This helps organizations to streamline their operations directly assessing Salesforce data in Snowflake for analysis and decision-making.

Data Analytics 40

Data Analytics MySQL PostgreSQL Data Lake 40

ProjectPro

JUNE 6, 2025

These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. These Apache Spark projects are mostly into link prediction, cloud hosting, data analysis, and speech analysis. Data Migration RDBMSs were inefficient and failed to manage the growing demand for current data.

Hadoop 40

Hadoop Project Big Data Scala 40

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 40

Data Integration Project Data Lake Hospitality 40

ProjectPro

JUNE 6, 2025

MongoDB is one of the hottest IT tech skills in demand with big data and cloud proliferating the market. Companies are realizing the need for alternative NoSQL databases like MongoDB to develop operational applications that can drive business engagement at one tenth of the cost over RDBMS.

NoSQL 40

NoSQL MongoDB Certification Database 40

ProjectPro

JUNE 6, 2025

Experts predict that by 2025, the global big data and data engineering market will reach $125.89 billion, and those with skills in cloud-based ETL tools and distributed systems will be in the highest demand. As more organizations shift to the cloud, the demand for ETL engineers with expertise in these platforms is soaring.

Data Engineering 40

Data Engineering Data Engineer Engineering ETL Tools 40

ProjectPro

JUNE 6, 2025

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. It not only consumes more memory but also slackens data transfer.

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

Snowflake

JUNE 13, 2024

The journey toward achieving a robust data platform that secures all your data in one place can seem like a daunting one. But at Snowflake, we’re committed to making the first step the easiest — with seamless, cost-effective data ingestion to help bring your workloads into the AI Data Cloud with ease.

Data Ingestion 115

Data Ingestion MySQL PostgreSQL Data Pipeline 115

ProjectPro

JUNE 6, 2025

Fusion RAG Architecture Fusion RAG extends the retrieval process by combining information from multiple sources—structured (like relational databases or APIs) and unstructured (documents, PDFs, or web pages). Image Source: Google Cloud Skills Boost 3. Reference Research Paper: [link] 4.

Architecture 52

Architecture Data Ingestion Google Cloud AWS 52

U-Next

MARCH 1, 2023

Introduction Data Engineer is responsible for managing the flow of data to be used to make better business decisions. A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. What is AWS Kinesis?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Knowledge Hut

NOVEMBER 2, 2023

As an AWS Cloud Practitioner with experience in delivering multiple AWS cloud practitioner projects, I vividly recall assisting a startup to prove the scalability of their AI solution on AWS during one of my early projects. This experience ignited my passion for architecting cost-effective, scalable solutions on the AWS platform.

AWS 52

AWS Coding Cloud Project 52

ProjectPro

JUNE 6, 2025

Hadoop's distributed computing design enables it to handle large data volumes, giving more processing power when using more nodes. Also, Hadoop retains data without the need for preprocessing. Tableau's popularity stems from its ability to connect to various data sources.

Data Science 40

Data Science Hadoop Unstructured Data Machine Learning 40

ProjectPro

JUNE 6, 2025

In 2024, the data engineering job market is flourishing, with roles like database administrators and architects projected to grow by 8% and salaries averaging $153,000 annually in the US (as per Glassdoor ). These trends underscore the growing demand and significance of data engineering in driving innovation across industries.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

ProjectPro

JUNE 6, 2025

Characteristics of a Data Science Pipeline Data Science Pipeline Workflow Data Science Pipeline Architecture Building a Data Science Pipeline - Steps Data Science Pipeline Tools 5 Must-Try Projects on Building a Data Science Pipeline Master Building Data Pipelines with ProjectPro!

Data Science 40

Data Science Building AWS Data Lake 40

ProjectPro

JUNE 6, 2025

It is suitable in scenarios where data needs to be collected from different systems, transformed, and loaded into a central repository. AWS Data Pipeline AWS Data Pipeline is a cloud-based service by Amazon Web Services (AWS) that simplifies the orchestration of data workflows. PREVIOUS NEXT <

Data Pipeline 40

Data Pipeline Building Retail Data Ingestion 40

ProjectPro

JUNE 6, 2025

Traditional data tools cannot handle this massive volume of complex data, so several unique Big Data software tools and architectural solutions have been developed to handle this task. Big Data Tools extract and process data from multiple data sources. Why Are Big Data Tools Valuable to Data Professionals?

Big Data Tools 40

Big Data Tools Big Data Hadoop Kafka 40

ProjectPro

JUNE 6, 2025

Vendor-Specific Data Engineering Certifications The vendor-specific data engineer certifications help you enhance your knowledge and skills relevant to specific vendors, such as Azure, Google Cloud Platform, AWS, and other cloud service vendors. Build a unique job-winning data engineer resume with big data mini projects.

Certification 40

Certification Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

Data Analysis Tools- How does Big Data Analytics Benefit Businesses? Big data is much more than just a buzzword. 95 percent of companies agree that managing unstructured data is challenging for their industry. Big data analysis tools are particularly useful in this scenario.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

ProjectPro

JUNE 6, 2025

"Data modelers are like architects who design and plan the structure of a building before it's constructed. Transform unstructured data into structured data by fixing errors, redundancies, missing numbers, and other anomalies, eliminating unnecessary data, optimizing data systems, and finding relevant insights.

NoSQL 40

NoSQL ETL Tools SQL Certification 40

ProjectPro

FEBRUARY 8, 2023

For e.g., Finaccel, a leading tech company in Indonesia, leverages AWS Glue to easily load, process, and transform their enterprise data for further processing. Another leading European company, Claranet, has adopted Glue to migrate their data load from their existing on-premise solution to the cloud. How Does AWS Glue Work?

AWS 98

AWS Scala Metadata Data Lake 98

ProjectPro

JUNE 6, 2025

Capital One leverages AWS to transform data into valuable insights using machine learning, enabling the company to innovate rapidly on behalf of its customers. In supervised learning, the algorithm is trained on labeled data. In unsupervised learning, the algorithm seeks to identify patterns in unstructured data.

Machine Learning 75

Machine Learning Algorithm Amazon Web Services Healthcare 75