Precisely

JANUARY 9, 2025

The demand for higher data velocity, faster access and analysis of data as its created and modified without waiting for slow, time-consuming bulk movement, became critical to business agility. Which turned into data lakes and data lakehouses Poor data quality turned Hadoop into a data swamp, and what sounds better than a data swamp?

Data Integration 119

Data Integration Data Warehouse Data Lake Hadoop 119

Christophe Blefari

MARCH 1, 2023

In the ELT, the load is done before the transform part without any alteration of the data leaving the raw data ready to be transformed in the data warehouse. In a simple words dbt sits on top of your raw data to organise all your SQL queries that are defining your data assets.

Data Warehouse 278

Data Warehouse Metadata SQL Raw Data 278

ProjectPro

JUNE 6, 2025

The demand for data-related roles has increased massively in the past few years. Companies are actively seeking talent in these areas, and there is a huge market for individuals who can manipulate data, work with large databases and build machine learning algorithms. Have you thought about what happens when more data comes in?

Engineering 75

Engineering Deep Learning Software Engineering Software Engineer 75

Cloudera

DECEMBER 4, 2024

All this by making it easier for customers to connect their workloads with Snowflake, Cloudera, and unique AWS services such as Amazon Simple Storage Service (Amazon S3), Amazon Elastic Kubernetes Service (Amazon EKS) , Amazon Relational Database Service (Amazon RDS), Amazon Elastic Compute Cloud (Amazon EC2), Amazon EMR and Amazon Athena.

AWS 89

AWS Raw Data Relational Database Government 89

Engineering at Meta

JANUARY 21, 2025

However, Strobelight has several safeguards in place to prevent users from causing performance degradation for the targeted workloads and retention issues for the databases Strobelight writes to. Strobelight also delays symbolization until after profiling and stores raw data to disk to prevent memory thrash on the host.

Technology 115

Technology Metadata Utilities Engineering 115

ProjectPro

JUNE 6, 2025

But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses.

AWS 66

AWS Scala Metadata Data Lake 66

Teradata

MAY 30, 2025

In Vantage, this refers to a database name, which you will need to configure your dbt project. The tables, products, purchases, and users, are the primary entities being synced from the source Sample Data (Faker) to the destination Teradata Vantage. sources: Contains source configuration files for the raw data sources.

Data Integration 52

Data Integration Raw Data Metadata Data Pipeline 52

Ascend.io

OCTOBER 28, 2024

What is Data Transformation? Data transformation is the process of converting raw data into a usable format to generate insights. It involves cleaning, normalizing, validating, and enriching data, ensuring that it is consistent and ready for analysis.

Raw Data 52

Raw Data Aggregated Data Data Pipeline Data Validation 52

Analytics Vidhya

JUNE 12, 2023

Introduction Meet Tajinder, a seasoned Senior Data Scientist and ML Engineer who has excelled in the rapidly evolving field of data science. Tajinder’s passion for unraveling hidden patterns in complex datasets has driven impactful outcomes, transforming raw data into actionable intelligence.

Machine Learning 185

Machine Learning Engineering Raw Data Data Science 185

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. Table of Contents AWS Redshift Data Warehouse Architecture 1. Client Applications 2.

Data Pipeline 64

Data Pipeline AWS Project Building 64

ProjectPro

JUNE 6, 2025

Data engineers can gain insights from data with Redshift Serverless by easily importing and querying data in the data warehouse. Additionally, engineers can build schemas and tables, import data visually, and explore database objects using Query Editor v2.

AWS 52

AWS Data Engineering Data Engineer Engineering 52

ProjectPro

JUNE 6, 2025

Today, data engineers are constantly dealing with a flood of information and the challenge of turning it into something useful. The journey from raw data to meaningful insights is no walk in the park. It requires a skillful blend of data engineering expertise and the strategic use of tools designed to streamline this process.

Data Pipeline 49

Data Pipeline Google Cloud AWS Kafka 49

ProjectPro

JUNE 6, 2025

TensorFlow) Strong communication and presentation skills Data Scientist Salary According to the Payscale, Data Scientists earn an average of $97,680. Data Analysts Roles and Responsibilities The day-to-day job description of a data analyst is as follows: Conduct surveys to collect raw data.

Data Science 56

Data Science Data Mining Data Architect BI 56

ProjectPro

JUNE 6, 2025

Emily is an experienced big data professional in a multinational corporation. As she deals with vast amounts of data from multiple sources, Emily seeks a solution to transform this raw data into valuable insights. dbt and Snowflake: Building the Future of Data Engineering Together."

Pipeline-centric 40

Pipeline-centric Database-centric Raw Data Data Warehouse 40

ProjectPro

JUNE 6, 2025

If you are still wondering whether or why you need to master SQL for data engineering, read this blog to take a deep dive into the world of SQL for data engineering and how it can take your data engineering skills to the next level. Data engineers can perform any quality checks using the DDL commands in SQL.

Data Engineering 45

Data Engineering Data Engineer SQL Engineering 45

The Pragmatic Engineer

JUNE 13, 2023

Agoda co-locates in all data centers, leasing space for its racks and the largest data center consumes about 1 MW of power. It uses Spark for the data platform. For transactional databases, it’s mostly the Microsoft SQL Server, but also other databases like PostgreSQL, ScyllaDB and Couchbase.

Cloud 242

Cloud Utilities Database BI 242

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. by ingesting raw data into a cloud storage solution like AWS S3. Use the ESPNcricinfo Ball-by-Ball Dataset to process match data.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

ProjectPro

JUNE 6, 2025

This function also allows DBT to automatically handle schema changes and cross-database functionality, improving manageability within your project. You can use the source function to reference the raw tables directly in your models by defining a source in your sources.yml file.

Raw Data 40

Raw Data SQL Datasets Data Pipeline 40

Snowflake

NOVEMBER 11, 2024

Deliver multimodal analytics with familiar SQL syntax Database queries are the underlying force that runs the insights across organizations and powers data-driven experiences for users. Traditionally, SQL has been limited to structured data neatly organized in tables.

Unstructured Data 98

Unstructured Data SQL AWS Healthcare 98

ProjectPro

JUNE 6, 2025

ELT involves three core stages- Extract- Importing data from the source server is the initial stage in this process. Load- The pipeline copies data from the source into the destination system, which could be a data warehouse or a data lake. Scalability ELT can be highly adaptable when using raw data.

Data Engineering 40

Data Engineering Data Engineer Engineering Data Lake 40

Analytics Vidhya

FEBRUARY 25, 2023

The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Cloud Storage 162

Cloud Storage Data Lake Cloud Unstructured Data 162

ProjectPro

JUNE 6, 2025

Similarly, companies with vast reserves of datasets and planning to leverage them must figure out how they will retrieve that data from the reserves. A data engineer a technical job role that falls under the umbrella of jobs related to big data. for working on cloud data warehouses.

Data Engineering 58

Data Engineering Data Engineer Engineering Amazon Web Services 58

ProjectPro

JUNE 6, 2025

However, the modern data ecosystem encompasses a mix of unstructured and semi-structured data—spanning text, images, videos, IoT streams, and more—these legacy systems fall short in terms of scalability, flexibility, and cost efficiency. That’s where data lakes come in. daily sales reports from an ERP system).

Data Lake 40

Data Lake Building Hadoop Raw Data 40

ProjectPro

JUNE 6, 2025

Graduating from ETL Developer to Data Engineer Career transitions come with challenges. Suppose you are already working in the data industry as an ETL developer. You can easily transition to other data-driven jobs such as data engineer , analyst, database developer, and scientist.

Data Engineering 59

Data Engineering Data Engineer Engineering ETL Tools 59

ProjectPro

JUNE 6, 2025

That enables users to execute tasks across vast systems, including external databases, cloud services, and big data technologies. After a data pipeline's structure has been defined as DAGs, Apache Airflow allows a user to specify a scheduled interval for every DAG. How are Pipelines Scheduled and Executed in Apache Airflow?

Data Pipeline 45

Data Pipeline Building Data Lake Raw Data 45

ProjectPro

JUNE 6, 2025

Building data pipelines is a core skill for data engineers and data scientists as it helps them transform raw data into actionable insights. You’ll walk through each stage of the data processing workflow, similar to what’s used in production-grade systems. b64encode(creds.encode()).decode()

Python 40

Python Building PostgreSQL Raw Data 40

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. The journey begins with collecting data from various sources, including internal databases, external repositories, and third-party providers.

Data Science 40

Data Science Building AWS Data Lake 40

ProjectPro

JUNE 6, 2025

Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives. While data warehouses contain transformed data, data lakes contain unfiltered and unorganized raw data.

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

ProjectPro

JUNE 6, 2025

You have probably heard the saying, "data is the new oil". It is extremely important for businesses to process data correctly since the volume and complexity of raw data are rapidly growing. EHR data allows practitioners and researchers to improve patient outcomes and health-related decision-making.

BI 45

BI ETL Tools Retail Healthcare 45

ProjectPro

JUNE 6, 2025

The field of data engineering is focused on ensuring that data is accessible, reliable, and easily processed by other teams within an organization, such as data analysts and data scientists. It involves various technical skills, including database design, data modeling, and ETL (Extract, Transform, Load) processes.

Data Engineering 49

Data Engineering Data Engineer Engineering Hadoop 49

ThoughtSpot

JANUARY 15, 2025

Thats why were excited to announce the launch of Analyst Studio , the collaborative creator space where data teams can come together to transform raw data into actionable insights. In fact, in this age of AI, we need analysts more now than ever.

BI 64

BI SQL Data Warehouse Raw Data 64

ProjectPro

JUNE 6, 2025

With so much riding on the efficiency of ETL processes for data engineering teams, it is essential to take a deep dive into the complex world of ETL on AWS to take your data management to the next level. AWS provides various relational and non-relational data stores that act as data sources in an ETL pipeline.

AWS 40

AWS Data Management Management ETL Tools 40

ProjectPro

JUNE 6, 2025

If someone is looking to master the art and science of constructing batch pipelines, ProjectPro has got you covered with this comprehensive tutorial that will help you learn how to build your first batch data pipeline and transform raw data into actionable insights. Data Storage- Processed data needs a destination for storage.

Data Pipeline 40

Data Pipeline Building Retail Data Ingestion 40

ProjectPro

JUNE 6, 2025

Top 3 Azure Databricks Delta Lake Project Ideas for Practice The following are a few projects involving Delta lake: ETL on Movies data This project involves ingesting data from Kafka and building Medallion architecture ( bronze, silver, and gold layers) Data Lakehouse. To understand more, visit this GitHub repository.

Data Lake 63

Data Lake Data Warehouse Metadata Unstructured Data 63

ProjectPro

JUNE 6, 2025

Extraction- Data is extracted from multiple sources such as databases, applications, or files. Transformation- After extraction, the data undergoes transformation- cleaned, standardized, and modified to match the desired format. data warehouses). and, finally, loading (storing) it in a central location (e.g.,

Data Integration 40

Data Integration Project Data Lake Hospitality 40

ProjectPro

JUNE 6, 2025

Ready to ride the data wave from “ big data ” to “big data developer”? 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.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

Leveraging data in analytics, data science, and machine learning initiatives to provide business insights is becoming increasingly important as organizations' data production, sources, and types increase. Extract The extract step of the ETL process entails extracting data from one or more sources.

Project 40

Project Non-relational Database Business Analyst Relational Database 40