Ascend.io

JULY 28, 2023

Data pipelines are integral to business operations, regardless of whether they are meticulously built in-house or assembled using various tools. As companies become more data-driven, the scope and complexity of data pipelines inevitably expand. Ready to fortify your data management practice?

Data Pipeline 52

Data Pipeline Architecture Lambda Architecture Data Architecture 52

Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Pipelines need to grow faster than the cost to run them.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Ascend.io

MARCH 17, 2023

These engineering functions are almost exclusively concerned with data pipelines, spanning ingestion, transformation, orchestration, and observation — all the way to data product delivery to the business tools and downstream applications. Pipelines need to grow faster than the cost to run them.

Data Pipeline 52

Data Pipeline Datasets Data Software Engineer 52

Monte Carlo

MARCH 24, 2023

However, the data is not valid because the height information is incorrect – penguins have the height data for giraffes, and vice versa. The data doesn’t accurately represent the real heights of the animals, so it lacks validity. What is Data Integrity? How Do You Maintain Data Integrity?

Data Validation 52

Data Validation Data Integration Data Cleanse Data Pipeline 52

Data Engineering Podcast

JULY 3, 2022

Your newly mimicked datasets are safe to share with developers, QA, data scientists—heck, even distributed teams around the world. Shorten development cycles, eliminate the need for cumbersome data pipeline work, and mathematically guarantee the privacy of your data, with Tonic.ai. In fact, while only 3.5%

Data Integration 100

Data Integration MongoDB Scala MySQL 100

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. Each type of tool plays a specific role in the DataOps process, helping organizations manage and optimize their data pipelines more effectively.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Cloudera

FEBRUARY 15, 2024

Improved data accessibility: By providing self-service data access and analytics, modern data architecture empowers business users and data analysts to analyze and visualize data, enabling faster decision-making and response to regulatory requirements. This results in enhanced efficiency in compliance processes.

Insurance 86

Insurance Banking Data Architecture Data Ingestion 86

phData: Data Engineering

MARCH 8, 2023

In today’s increasingly data-driven world, businesses need reliable and efficient ways to collect, analyze, and draw insights from their data. With so many data integration tools available in the market, it can be difficult to determine which one is the best fit for your organization. What is Fivetran?

IT 96

IT Data Warehouse Data Ingestion Data Integration 96

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

Ascend.io

AUGUST 15, 2023

You require a comprehensive solution that addresses every facet, from ingestion and transformation to orchestration and reverse ETL. It’s no surprise, then, that the quest for Fivetran alternatives is on the rise as organizations set their sights on a more holistic data approach.

Data Management 52

Data Management Management Data Ingestion Data Pipeline 52

Ascend.io

JUNE 8, 2023

The Essential Six Capabilities To set the stage for impactful and trustworthy data products in your organization, you need to invest in six foundational capabilities. Data pipelines Data integrity Data lineage Data stewardship Data catalog Data product costing Let’s review each one in detail.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

DareData

JANUARY 30, 2023

In this post, we'll discuss some key data engineering concepts that data scientists should be familiar with, in order to be more effective in their roles. These concepts include concepts like data pipelines, data storage and retrieval, data orchestrators or infrastructure-as-code.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

DataKitchen

MAY 10, 2024

The Third of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Raw Data 49

Raw Data Data Ingestion Datasets Data 49

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional who is in charge of designing, implementing, and maintaining data processing systems and solutions on the Microsoft Azure cloud platform. A Data Engineer is responsible for designing the entire architecture of the data flow while taking the needs of the business into account.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Ascend.io

MARCH 1, 2023

Sounds like you need a new data quality solution, right? Apply Actionable Data Quality Directly in Your Data Pipelines Turns out you don’t need a new tool to address this common scenario. The fix will take an entire development cycle and run up more costs.

Data Pipeline 52

Data Pipeline Data Ingestion Data Data Integration 52

Ascend.io

FEBRUARY 20, 2023

Sounds like you need a new data quality solution, right? Apply Actionable Data Quality Directly in Your Data Pipelines Turns out you don’t need a new tool to address this common scenario. The fix will take an entire development cycle and run up more costs.

Data Pipeline 52

Data Pipeline Data Ingestion Data Data Integration 52

Ascend.io

FEBRUARY 20, 2023

Sounds like you need a new data quality solution, right? Apply Actionable Data Quality Directly in Your Data Pipelines Turns out you don’t need a new tool to address this common scenario. The fix will take an entire development cycle and run up more costs.

Data Pipeline 52

Data Pipeline Data Ingestion Data Data Integration 52

DataKitchen

OCTOBER 20, 2023

The Solution: ‘Payload’ Data Journeys Traditional Data Observability usually focuses on a ‘process journey,’ tracking the performance and status of data pipelines. ’ It assigns unique identifiers to each data item—referred to as ‘payloads’—related to each event.

Insurance 67

Insurance Pharmaceutical Data Data Ingestion 67

Knowledge Hut

MARCH 20, 2024

The job description for Azure data engineer that I have elucidated below focuses more on foundational tasks while providing opportunities for learning and growth within the field: Data ingestion: This role involves assisting in the process of collecting and importing data from various sources into Azure storage solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Knowledge Hut

SEPTEMBER 25, 2023

As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. You will be in charge of creating and maintaining data pipelines, data storage solutions, data processing, and data integration to enable data-driven decision-making inside a company.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

MARCH 15, 2024

The job description for Azure data engineer that I have elucidated below focuses more on foundational tasks while providing opportunities for learning and growth within the field: Data ingestion: This role involves assisting in the process of collecting and importing data from various sources into Azure storage solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Knowledge Hut

MARCH 28, 2024

Job Role 1: Azure Data Engineer Azure Data Engineers develop, deploy, and manage data solutions with Microsoft Azure data services. They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines. GDPR, HIPAA), and industry standards.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

DareData

JULY 5, 2023

Typically, it is advisable to retain the data in its original, unaltered format when transferring it from any source to the data lake layer. The Data Warehouse(s) facilitates data ingestion and enables easy access for end-users. If you need help to understand how these tools work, feel free to drop us a message!

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Ingestion 40

Data Ingestion Data Government Datasets 40

Monte Carlo

MAY 25, 2023

Picture this: your data is scattered. Data pipelines originate in multiple places and terminate in various silos across your organization. Your data is inconsistent, ungoverned, inaccessible, and difficult to use. Some of the value companies can generate from data orchestration tools include: Faster time-to-insights.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

Towards Data Science

NOVEMBER 4, 2023

I’d like to discuss some popular Data engineering questions: Modern data engineering (DE). Does your DE work well enough to fuel advanced data pipelines and Business intelligence (BI)? Are your data pipelines efficient? What is it? The downside of this approach is it’s pricing model though. Image by author.

Data Engineering 82

Data Engineering Data Engineer Engineering BI 82

Knowledge Hut

APRIL 25, 2023

Data engineering is a field that requires a range of technical skills, including database management, data modeling, and programming. Data engineering tools can help automate many of these processes, allowing data engineers to focus on higher-level tasks like extracting insights and building data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Edureka

FEBRUARY 7, 2023

Azure Data Engineers use a variety of Azure data services, such as Azure Synapse Analytics, Azure Data Factory, Azure Stream Analytics, and Azure Databricks, to design and implement data solutions that meet the needs of their organization. Gain hands-on experience using Azure data services.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Data integration , on the other hand, happens later in the data management flow.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

DataKitchen

SEPTEMBER 21, 2023

In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers. After navigating the complexity of multiple systems and stages to bring data to its end-use case, the final product’s value becomes the ultimate yardstick for measuring success.

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

Monte Carlo

NOVEMBER 14, 2023

However, it can be difficult to store certain types of data in the table format, like images, meaning that data will have to be stored elsewhere, adding greater complexity to your stack. As with any table format, Apache Iceberg tables are only as useful and reliable as the data stored in them.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Silectis

JANUARY 3, 2021

Data engineers design, build, and maintain data pipelines that transform data from a raw state to a useful one, ready for analysis or data science modeling. Data Integration Combining data from various, disparate sources into one unified view. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

AUGUST 24, 2021

Data Sourcing: Building pipelines to source data from different company data warehouses is fundamental to the responsibilities of a data engineer. So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. Google BigQuery receives the structured data from workers.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Rockset

NOVEMBER 28, 2022

First, CDC theoretically allows companies to analyze and react to data in real time, as it’s generated. It works with existing streaming systems like Apache Kafka, Amazon Kinesis, and Azure Events Hubs, making it easier than ever to build a real-time data pipeline. Striim : A unified data integration and streaming platform.

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB Data Pipeline 52

AltexSoft

MARCH 30, 2023

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Besides that, it’s fully compatible with various data ingestion and ETL tools.

Scala 64

Scala Data Lake BI Google Cloud 64

Striim

JULY 10, 2023

Additionally, Striim is a robust real-time data integration platform, which complements Databricks Unity Catalog by facilitating continuous data ingestion and synchronization. Note: To adhere to best practices, it is recommended to use Databricks Secrets Management for storing these credentials securely.

Python 40

Python Database Programming Language Coding 40