Ascend.io

SEPTEMBER 14, 2023

The rise of data-intensive operations has positioned data engineering at the core of today’s organizations. As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand. Why Python for Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Rockset

AUGUST 25, 2021

With Confluent’s recent IPO, streaming data has officially gone mainstream, “becoming the underpinning of a modern digital customer experience, and the key to driving intelligent, efficient operations” to quote from their letter to shareholders. This greatly reduces both the amount of data stored and the compute for queries.

Aggregated Data 52

Aggregated Data Data Lake Hadoop SQL 52

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.

SQL 52

SQL Kafka MongoDB MySQL 52

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. Cloud data warehouses solve these problems. Belonging to the category of OLAP (online analytical processing) databases, popular data warehouses like Snowflake, Redshift and Big Query can query one billion rows in less than a minute.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Warehouse? . Data Warehouse in DBMS: .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. ELT vs ETL. Order of process phases.

Process 52

Process Building Raw Data Data Lake 52

Databand.ai

JULY 10, 2023

Observability platforms gather, examine, and display telemetry data from various sources like logs, metrics, and trace data. This is part of a series of articles about data observability. An observability platform is a comprehensive solution that allows data engineers to monitor, analyze, and optimize their data pipelines.

Data Pipeline 52

Data Pipeline Algorithm Raw Data Aggregated Data 52

AltexSoft

JANUARY 26, 2022

As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Quoting a comment from the Reddit discussion , “Their [analytics engineers] job is to marry the technical requirements of the data stack with the business objectives”.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

ProjectPro

AUGUST 24, 2021

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? For beginners or peeps who are utterly new to the data industry, Data Scientist is likely to be the first job title they come across, and the perks of being one usually make them go crazy.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry. Why is Data Engineering In Demand?

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

DoorDash Engineering

APRIL 12, 2023

Metrics are vital for measuring success in any data-driven company, but ensuring that these metrics are consistently and accurately measured across the organization can be challenging. Dependency on SQL made it challenging for non-technical users to analyze experiments without assistance from data scientists.

SQL 82

SQL Metadata Raw Data Government 82