ProjectPro

JUNE 6, 2025

Data Science Pipeline Workflow The data science pipeline is a structured framework for extracting valuable insights from raw data and guiding analysts through interconnected stages. This phase demands meticulous attention to detail to acquire high-quality and relevant data.

Data Science 40

Data Science Building Data Lake Raw Data 40

AltexSoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JUNE 6, 2025

Today, businesses use traditional data warehouses to centralize massive amounts of raw data from business operations. Amazon Redshift is helping over 10000 customers with its unique features and data analytics properties. Amazon Redshift is a cloud data warehouse that stores structured and semi-structured data.

Data Pipeline 64

Data Pipeline AWS Project Building 64

ProjectPro

JUNE 6, 2025

Check out this blog that presents the Top 25 DBT Interview Questions and Answers – designed to equip you with the knowledge needed to excel in interviews and stand out in the competitive field of data analytics and engineering. Imagine your organization has a mix of structured and semi-structured data.

Raw Data 40

Raw Data SQL Data Pipeline Datasets 40

ProjectPro

JUNE 6, 2025

Most of us have observed that data scientist is usually labeled the hottest job of the 21st century, but is it the only most desirable job? No, that is not the only job in the data world. This project builds a comprehensive ETL and analytics pipeline, from ingestion to visualization, using Google Cloud Platform.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

ProjectPro

JUNE 6, 2025

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

JUNE 6, 2025

10 Must-Have Data Engineering Skills In this section, we will discuss the top skills for data engineers that are necessary if you are looking forward to become a data engineer. When working with real-world data, it may only sometimes be the case that the information is stored in rows and columns.

Data Engineering 49

Data Engineering Data Engineer Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

Top 10+ Tools For Data Engineers Worth Exploring in 2025 Let us look at the some of the best data engineering tools you should not miss exploring in 2022- 1. Apache Spark Apache Spark is an open-source data analytics engine with a customer base of over 52K organizations , including top companies like Apple, Microsoft, IBM, etc.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

ProjectPro

JUNE 6, 2025

This blog will help you determine which data analysis tool best fits your organization by exploring the top data analysis tools in the market with their key features, pros, and cons. The vast number of technologies available makes it challenging to start working in data analytics. Google Data Studio 10. Power BI 4.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

ProjectPro

JUNE 6, 2025

Your SQL skills as a data engineer are crucial for data modeling and analytics tasks. Making data accessible for querying is a common task for data engineers. Collecting the raw data, cleaning it, modeling it, and letting their end users access the clean data are all part of this process.

Data Engineering 45

Data Engineering Data Engineer SQL Engineering 45

ProjectPro

JUNE 6, 2025

As a result, having a central repository to safely store all data and further examine it to make informed decisions becomes necessary for enterprises. This is the reason why we need Data Warehouses. What is Snowflake Data Warehouse? What Does Snowflake Do?

Architecture 56

Architecture IT Data Warehouse Amazon Web Services 56

ProjectPro

JUNE 6, 2025

Read this blog to know more about the core AWS big data services essential for data engineering and their implementations for various purposes, such as big data engineering , machine learning, data analytics, etc. million organizations that want to be data-driven choose AWS as their cloud services partner.

AWS 40

AWS Data Engineering Data Engineer Engineering 40

Knowledge Hut

APRIL 25, 2024

You'll be better able to comprehend the complex ideas in this field if you have a solid understanding of the characteristics of big data in data analytics and a list of essential features for new data platforms. What Are the Different Features of Big Data Analytics?

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

ProjectPro

JUNE 6, 2025

Combining concepts of conciseness and functional paradigm with OOP and high-level performance, data engineers can use Scala equally for lightweight, user-facing applications and terabyte-level big data pipelines with Spark jobs and distributed systems. So, we can focus on some other transformation methods valid in data analytics.

Scala 40

Scala Data Engineering Data Engineer Engineering 40

Edureka

APRIL 14, 2025

Microsoft offers a leading solution for business intelligence (BI) and data visualization through this platform. It empowers users to build dynamic dashboards and reports, transforming raw data into actionable insights. However, it leans more toward transforming and presenting cleaned data rather than processing raw datasets.

BI 40

BI Business Intelligence Raw Data Retail 40

ProjectPro

JUNE 6, 2025

Here's an example of a job description of an ETL Data Engineer below: Source: www.tealhq.com/resume-example/etl-data-engineer Key Responsibilities of an ETL Data Engineer Extract raw data from various sources while ensuring minimal impact on source system performance.

Data Engineering 40

Data Engineering Data Engineer Engineering ETL Tools 40

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst. What Is Big Data Analytics?

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

JUNE 6, 2025

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. Get ready to expand your knowledge and take your big data career to the next level! “Data analytics is the future, and the future is NOW!

Big Data 40

Big Data Hadoop Relational Database NoSQL 40

ProjectPro

JUNE 6, 2025

It is difficult to stay up-to-date with the latest developments in IT industry especially in a fast growing area like big data where new big data companies, products and services pop up daily. With the explosion of Big Data, Big data analytics companies are rising above the rest to dominate the market.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

Edureka

JUNE 1, 2023

This is where AWS Data Analytics comes into action, providing businesses with a robust, cloud-based data platform to manage, integrate, and analyze their data. In this blog, we’ll explore the world of Cloud Data Analytics and a real-life application of AWS Data Analytics.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

ProjectPro

JUNE 6, 2025

When applied to data analysis, LLM-powered agents can process vast amounts of structured and unstructured data, extract patterns, generate meaningful insights, and forecast future trends with minimal human intervention. LLM-powered data analytics agents can be categorized based on their functionality and use cases.

Data Analysis 40

Data Analysis Building Raw Data Machine Learning 40

Striim

SEPTEMBER 11, 2024

Third-Party Data: External data sources that your company does not collect directly but integrates to enhance insights or support decision-making. These data sources serve as the starting point for the pipeline, providing the raw data that will be ingested, processed, and analyzed.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

ProjectPro

JUNE 6, 2025

Data wrangling is as essential to the data science process as the sun is important for plants to complete the process of photosynthesis. Data wrangling involves extracting the most valuable information from the data per a business's objectives and requirements. Table of Contents What is Data Wrangling in Data Science?

Raw Data 58

Raw Data Programming Language Unstructured Data Google Cloud 58

ProjectPro

JUNE 6, 2025

It involves connectors or agents that capture data in real-time from sources like IoT devices, social media feeds, sensors, or transactional systems using popular ingestion tools like Azure Synapse Analytics , Azure Event Hubs, Apache Kafka, or AWS Kinesis. The data is continually processed while it moves through the pipeline.

Data Ingestion 40

Data Ingestion Kafka Google Cloud AWS 40

Knowledge Hut

DECEMBER 26, 2023

Businesses benefit at large with these data collection and analysis as they allow organizations to make predictions and give insights about products so that they can make informed decisions, backed by inferences from existing data, which, in turn, helps in huge profit returns to such businesses. What is the role of a Data Engineer?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Precisely

OCTOBER 5, 2023

According to the 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, 77% of data and analytics professionals say data-driven decision-making is the top goal of their data programs. That’s where data enrichment comes in.

Raw Data 69

Raw Data Insurance Telecommunication Datasets 69

ProjectPro

JUNE 6, 2025

Python for ETL enables data engineers and analysts to automate and manage data pipelines, apply transformations, and handle data integration efficiently. It is a popular choice in data engineering and data analytics. Data Transformation: Raw data is rarely suitable for analysis.

Python 40

Python ETL Tools Data Warehouse Programming Language 40

ProjectPro

JUNE 6, 2025

Also, you will find some interesting data engineer interview questions that have been asked in different companies (like Facebook, Amazon, Walmart, etc.) that leverage big data analytics and tools. Preparing for data engineer interviews makes even the bravest of us anxious. Structured data usually consists of only text.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Data Lake MongoDB 59

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. Autonomous data warehouse from Oracle. . What is Data Lake? . Essentially, a data lake is a repository of raw data from disparate sources.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. However, data warehouses can experience limitations and scalability challenges.

Data Management 52

Data Management Management Data Lake Data Governance 52

Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

APRIL 23, 2024

Data Science is the field that focuses on gathering data from multiple sources using different tools and techniques. Whereas, Business Intelligence is the set of technologies and applications that are helpful in drawing meaningful information from raw data. Business Intelligence only deals with structured data.

Business Intelligence 52

Business Intelligence Data Science BI Unstructured Data 52

Knowledge Hut

SEPTEMBER 26, 2023

Workspace is the platform where power BI developers create reports, dashboards, data sets, etc. Dataset is the collection of raw data imported from various data sources for the purpose of analysis. DirectQuery and Live Connection: Connecting to data without importing it, ideal for real-time or large datasets.

BI 52

BI Business Intelligence Raw Data Certification 52

Knowledge Hut

JANUARY 30, 2024

In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?

Database-centric 52

Database-centric ETL Tools Data Mining Data Cleanse 52