The Modern Data Company

APRIL 12, 2023

The market’s technical talent shortage and the high demand for analytics experts can make it difficult for healthcare organizations to find and retain the in-house expertise they need to design, deploy, and maintain cutting-edge data solutions.

Healthcare 98

Healthcare Hospitality Medical Electronics 98

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Knowledge Hut

SEPTEMBER 25, 2023

Who is an Azure Data Engineer? As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. They are in charge of designing data storage systems that scale, perform, and are economical enough to satisfy the organization's requirements.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

NOVEMBER 17, 2023

Azure Data Engineers play an important role in building efficient, secure, and intelligent data solutions on Microsoft Azure's powerful platform. The position of Azure Data Engineers is becoming increasingly important as businesses attempt to use the power of data for strategic decision-making and innovation.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

NOVEMBER 17, 2023

Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Storage, Azure Data Lake, Azure Blob Storage, Azure Cosmos DB, Azure Stream Analytics, Azure HDInsight, and other Azure data services are just a few of the many Azure data services that Azure data engineers deal with.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

MARCH 28, 2024

Azure Data Engineer Career Demands & Benefits Azure has become one of the most powerful platforms in the industry, where Microsoft offers a variety of data services and analytics tools. As a result, organizations are looking to capitalize on cloud-based data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. This approach ensures that only processed and refined data is housed in the data warehouse, leaving the raw data outside of it.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Knowledge Hut

MARCH 20, 2024

Speaking from experience, the data engineers in this role are right in the thick of it all. From start to finish, Azure data engineer roles and responsibilities revolve around designing, implementing, and managing data solutions specifically tailored for the Azure platform. Who is Azure Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Certification 52

Knowledge Hut

MARCH 15, 2024

Speaking from experience, the data engineers in this role are right in the thick of it all. From start to finish, Azure data engineer roles and responsibilities revolve around designing, implementing, and managing data solutions specifically tailored for the Azure platform. Who is Azure Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Certification 52

Ascend.io

JULY 3, 2024

Today, we’ll break down the key benefits, best practices, and implementation strategies to enhance your data workflows with Dataops. DataOps, short for Data Operations, is an emerging discipline that combines data engineering, data integration, and data quality with agile methodologies and DevOps practices.

Data Workflow 52

Data Workflow Data Pipeline Data Data Engineering 52

Knowledge Hut

DECEMBER 28, 2023

This blog will guide us through the Azure Data Engineer certification path , equipping us with insights necessary for this transformative journey. Who is an Azure Data Engineer? An Azure Data Engineer is responsible for designing, implementing and managing data solutions on Microsoft Azure.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Ascend.io

JULY 3, 2024

Today, we’ll break down the key benefits, best practices, and implementation strategies to enhance your data workflows with Dataops. DataOps, short for Data Operations, is an emerging discipline that combines data engineering, data integration, and data quality with agile methodologies and DevOps practices.

Data Workflow 52

Data Workflow Data Pipeline Data Data Engineering 52

Precisely

MAY 2, 2024

These processes are prone to errors, and poor-quality data can lead to delays in order processing and a host of downstream shipping and invoicing problems that put your customer relationships at risk. It’s clear that automation transforms the way we work, in SAP customer master data processes and beyond.

Coding Skills 69

Coding Skills Food Data Portfolio 69

Striim

AUGUST 22, 2024

Streams of data are continuously queried with Streaming SQL , enabling correlation, anomaly detection, complex event processing, artificial intelligence/machine learning, and live visualization. Because of this, streaming analytics is especially impactful for fraud detection, log analysis, and sensor data processing use cases.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Knowledge Hut

NOVEMBER 19, 2023

Azure Data Engineer Tools encompass a set of services and tools within Microsoft Azure designed for data engineers to build, manage, and optimize data pipelines and analytics solutions. These tools help in various stages of data processing, storage, and analysis. Let’s read about them in the next section.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

Knowledge Hut

JUNE 30, 2023

The essential theories, procedures, and equipment for creating trustworthy and effective data systems are covered in this book. It explores subjects including data modeling, data pipelines, data integration, and data quality, offering helpful advice on organizing and implementing reliable data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

DECEMBER 27, 2023

Big data analytics helps companies to identify customer related trends and patterns, analyze customer behavior thus helping businesses to find ways to satisfy and retain customers and fetch new ones. Pros : Highly scalable, provides fast access to data and is useful for R&D purposes. Offers flexibility and faster data processing.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

AltexSoft

FEBRUARY 11, 2023

Sample of a high-level data architecture blueprint for Azure BI programs. Source: Pragmatic Works This specialist also oversees the deployment of the proposed framework as well as data migration and data integration processes. But first, all candidates must be accredited by Arcitura as Big Data professionals.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

DECEMBER 29, 2023

Learning Outcomes: You will understand the processes and technology necessary to operate large data warehouses. Engineering and problem-solving abilities based on Big Data solutions may also be taught. Additionally, you will learn how to design and manage data processing systems.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

The Modern Data Company

MAY 8, 2023

Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses. It stores structured and unstructured data, enables schema-on-read and schema-on-write, and supports real-time data processing and analytics.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses. It stores structured and unstructured data, enables schema-on-read and schema-on-write, and supports real-time data processing and analytics.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses. It stores structured and unstructured data, enables schema-on-read and schema-on-write, and supports real-time data processing and analytics.

Data Management 52

Data Management Management Data Lake Data Governance 52

Databand.ai

DECEMBER 13, 2022

1) Joseph Machado Senior Data Engineer at LinkedIn Joseph is an experienced data engineer, holding a Master’s degree in Electrical Engineering from Columbia University and having spent time on the teams at Annalect, Narrativ, and most recently LinkedIn. He is also an AWS Certified Solutions Architect and AWS Certified Big Data expert.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Volume Big Data refers to large volumes of data, typically in the order of terabytes or petabytes. It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques. What Should You Choose Between Big Data and Small Data?

Big Data 52

Big Data Datasets Data Analysis Media 52

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. Don’t they all do the same thing? Is this the paradox of choice?

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

ProjectPro

JANUARY 31, 2022

The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market. Snowflake allows data to be examined and cleaned immediately, assuring data integrity.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

The Modern Data Company

APRIL 15, 2024

The Role of a Data Model Explained Think of a data model as the ultimate organizer in the vast library of your company’s data. Its job, from its position near the end of the data processing line, is similar to that of a librarian who: Answers queries from various departments looking for specific insights.

Government 52

Government Metadata Data Data Management 52

phData: Data Engineering

AUGUST 11, 2023

Data engineering models can help public health systems identify isolated cases before they explode into a health crisis. In Australia, the government’s healthcare branch uses Data Integration Partnership for Australia (DIPA) to identify adverse events. FAQs Which type of data is most beneficial for healthcare?

Healthcare 52

Healthcare Data Engineering Data Engineer Hospitality 52

ProjectPro

AUGUST 21, 2015

Big Data Hadoop Interview Questions and Answers These are Hadoop Basic Interview Questions and Answers for freshers and experienced. Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Best suited for OLTP and complex ACID transactions.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

MAY 31, 2021

For such scenarios, data-driven integration becomes less comfortable, so you must prefer event-based data integration. This project will teach you how to design and implement an event-based data integration pipeline on the Google Cloud Platform by processing data using DataFlow.

Big Data 52

Big Data Coding Project Hadoop 52

phData: Data Engineering

SEPTEMBER 27, 2024

But persistent staging is typically more structured and integrated into your overall customer data pipeline. It’s not just a dumping ground for data, but a crucial step in your customer data processing workflow. We’re increasingly living in the now with real-time customer data architectures.

Data 52

Data Raw Data Data Lake Architecture 52

RandomTrees

MARCH 17, 2025

Businesses are no longer just collecting data; they are looking to connect it , transform it , and leverage it for valuable insights in real-time. This is where Airbyte , the open-source data integration platform, is redefining the game. Airbyte supports both batch and real-time data integration.

Data Integration 52

Data Integration ETL Tools Data Workflow Data Pipeline 52

Precisely

JANUARY 6, 2025

While these systems provide flexibility and scalability, they also pose significant challenges for integrating, normalizing, and analyzing data. Thats where the concept of data streaming pipelines comes into play. Metadata-driven governance: Leveraging metadata to understand, troubleshoot, and optimize data processes.

Data Architecture 59

Data Architecture Architecture Pipeline-centric Banking 59