DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs. Have I Checked The Raw Data And The Integrated Data?

Raw Data 50

Raw Data Data Ingestion Datasets Data 50

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is the role of a Data Engineer? They are also accountable for communicating data trends. These are as follows: 1.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Workfall

JULY 18, 2023

In the vast realm of data engineering and analytics, a tool emerged that felt like a magical elixir. DBT , the Data Build Tool. Think of DBT as the trusty sidekick that accompanies data analysts and engineers on their quests to transform raw data into golden insights.

Datasets 77

Datasets Entertainment Data Data Workflow 77

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

Ascend.io

DECEMBER 11, 2023

Data orchestration is the process of efficiently coordinating the movement and processing of data across multiple, disparate systems and services within a company. Not every team needs data orchestration. However, this approach quickly shows its limitations as data volume escalates.

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

Ascend.io

JULY 11, 2024

Metadata is the information that provides context and meaning to data, ensuring it’s easily discoverable, organized, and actionable. It enhances data quality, governance, and automation, transforming raw data into valuable insights. This is what managing data without metadata feels like. Chaos, right?

Metadata 52

Metadata IT Government High Quality Data 52

Snowflake

MARCH 27, 2023

It seems everyone has a handful of such shapes in their raw data, and in the past they had to fix those shapes outside of Snowflake before ingesting them. Workflows automates not only geospatial processes, but other data workflows as well.

Generalist 52

Generalist Raw Data Business Analyst SQL 52

ProjectPro

JANUARY 20, 2016

If you want to work with big data , then learning Hadoop is a must - as it is becoming the de facto standard for big data processing. Apache Pig helps SQL server professionals create parallel data workflows. Apache pig eases data manipulation over multiple data sources using a combination of tools.

Hadoop 52

Hadoop SQL Java Big Data 52

Workfall

JULY 4, 2023

Reading Time: 8 minutes In the world of data engineering, a mighty tool called DBT (Data Build Tool) comes to the rescue of modern data workflows. Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights.

Data Warehouse 69

Data Warehouse SQL Database PostgreSQL 69

Knowledge Hut

DECEMBER 28, 2023

An Azure Data Engineer is responsible for designing, implementing and managing data solutions on Microsoft Azure. The Azure Data Engineer certification imparts to them a deep understanding of data processing, storage and architecture. It also shows that they can manage data workflows across various Azure services.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

phData: Data Engineering

SEPTEMBER 29, 2023

In reality, though, if you use data (read: any information), you are most likely practicing some form of data engineering every single day. Classically, data engineering is any process involving the design and execution of systems whose primary purpose is collecting and preparing raw data for user consumption.

Data Engineering 52

Data Engineering Data Engineer Engineering Algorithm 52

Databand.ai

AUGUST 30, 2023

Unified DataOps represents a fresh approach to managing and synchronizing data operations across several domains, including data engineering, data science, DevOps, and analytics. The goal of this strategy is to streamline the entire process of extracting insights from raw data by removing silos between teams and technologies.

Data Governance 40

Data Governance Data Cleanse Government Data Science 40

Edureka

JULY 3, 2024

Companies are drowning in a sea of raw data. As data volumes explode across enterprises, the struggle to manage, integrate, and analyze it is getting real. Thankfully, with serverless data integration solutions like Azure Data Factory (ADF), data engineers can easily orchestrate, integrate, transform, and deliver data at scale.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

Monte Carlo

JUNE 14, 2023

5 Data pipeline architecture designs and their evolution The Hadoop era , roughly 2011 to 2017, arguably ushered in big data processing capabilities to mainstream organizations. Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Striim

MARCH 13, 2025

These compact numerical representations of data not only facilitate enhanced data analysis but also improve search capabilities and machine learning tasks. Striim has harnessed the power of vector embeddings to provide its customers with a robust tool for transforming raw data into meaningful insights in real-time.

Data Process 52

Data Process Process Raw Data Machine Learning 52

Cloudera

DECEMBER 4, 2024

For example: An AWS customer using Cloudera for hybrid workloads can now extend analytics workflows to Snowflake, gaining deeper insights without moving data across infrastructures. Or now customers can combine Cloudera’s raw data processing and Snowflake’s analytical capabilities to build efficient AI/ML pipelines.

AWS 89

AWS Raw Data Relational Database Government 89