Monte Carlo

JUNE 2, 2024

Monitoring and Ensuring Data Quality and Performance: In 68% of job postings, engineers use data observability tools such as Monte Carlo to monitor the health and performance of data systems, ensuring data quality, detecting anomalies, and troubleshooting issues to keep data pipelines reliable.

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Monte Carlo

JUNE 2, 2024

Monitoring and Ensuring Data Quality and Performance: In 68% of job postings, engineers use data observability tools such as Monte Carlo to monitor the health and performance of data systems, ensuring data quality, detecting anomalies, and troubleshooting issues to keep data pipelines reliable.

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Knowledge Hut

MARCH 20, 2024

An Azure Data Engineer is a professional specializing in designing, implementing, and managing data solutions on the Microsoft Azure cloud platform. They possess expertise in various aspects of data engineering. As an Azure data engineer myself, I was responsible for managing data storage, processing, and analytics.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Knowledge Hut

MARCH 15, 2024

An Azure Data Engineer is a professional specializing in designing, implementing, and managing data solutions on the Microsoft Azure cloud platform. They possess expertise in various aspects of data engineering. As an Azure data engineer myself, I was responsible for managing data storage, processing, and analytics.

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

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

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

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. A notebook-based environment allows data engineers, data scientists, and analysts to work together seamlessly, streamlining data processing, model development, and deployment.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

APRIL 25, 2023

Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases. Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Databand.ai

JUNE 28, 2023

Yet reality is of course more closely governed by Murphy’s law, and on the output side of the black box, you will often see a host of strange values and cryptic missing columns. Data engineers are scratching their heads and realizing that to correct, you must first observe. And why the discrepancy?

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Knowledge Hut

SEPTEMBER 29, 2023

Microsoft Data Engineer Certification is one such certification which is most sought after by professionals. By combining data from various structured and unstructured data systems into structures, Microsoft Azure Data Engineers will be able to create analytics solutions.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

ProjectPro

FEBRUARY 21, 2023

GCP Data Engineer Certification The Google Cloud Certified Professional Data Engineer certification is ideal for data professionals whose jobs generally involve data governance, data handling, data processing, and performing a lot of feature engineering on data to prepare it for modeling.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

AUGUST 18, 2023

This certification covers fundamental concepts such as cloud computing architecture, GCP services, & data storage & processing. In addition, candidates need to have their government-issued ID proof, such as a driver's license, passport, or any other government ID, to appear for the exam. (d)

Google Cloud 52

Google Cloud Certification Cloud Cloud Computing 52

Snowflake

NOVEMBER 29, 2023

While the former can be solved by tokenization strategies provided by external vendors, the latter mandates the need for patient-level data enrichment to be performed with sufficient guardrails to protect patient privacy, with an emphasis on auditability and lineage tracking. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 83

Metadata Healthcare Medical Data Storage 83

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Snowflake

JUNE 5, 2024

By using Cortex, enterprises can bring AI directly to the governed data to quickly extend access and governance policies to the models. Cortex Search manages the end-to-end workflow for data ingestion, embedding, retrieval, reranking and generation. Our state-of-the-art hybrid search enables better results.

Coding 86

Coding Building Management Government 86

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. Amazon S3 for AWS, Azure Blob Storage for Azure, or Google Cloud Storage for GCP) to store the actual data files in micro-partitions.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Potential downsides of data lakes include governance and integration challenges. Data lakes often lack robust data governance, leading to data quality, consistency, and security issues. Data Lakehouse: Bridging Data Worlds A data lakehouse combines the best features of data lakes and data warehouses.

Data Management 52

Data Management Data Lake Management Data Governance 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? 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. Despite Hadoop’s parallel and distributed processing, compute was a limited resource as well.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

phData: Data Engineering

JANUARY 3, 2022

This means it’s business-critical that companies can derive value from their data to better inform business decisions, protect their enterprise and their customers, and grow their business. This comprehensive guide will cover all of the basics of data engineering including common roles, functions, and responsibilities.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

AltexSoft

JULY 29, 2022

According to the latest report by Allied Market Research , the Big Data platform will see the biggest rise in adoption in telecommunication, healthcare, and government sectors. Hadoop distributed file system or HDFS is a data storage technology designed to handle gigabytes to terabytes or even petabytes of data.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

SEPTEMBER 21, 2023

Besides Elasticsearch, which is the hub for indexing, searching, and complex data analytics, the stacks include the following tools Beats are lightweight data shippers that are part of the Elastic Stack. Beats facilitate data movement from source to destination, which can be either Elasticsearch or Logstash, depending on the use case.

Engineering 52

Engineering NoSQL Programming Language Java 52

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data NoSQL Data Lake Hadoop 44

ProjectPro

NOVEMBER 15, 2021

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Calcite has chosen to stay out of the data storage and processing business.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

MAY 12, 2023

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. The process requires extracting data from diverse sources, typically via APIs.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

MAY 31, 2021

Personal data privacy and protection are becoming increasingly crucial, and you should prioritize them immediately as you embark on your big data journey. You must consolidate all your data initiatives, sources, and datasets into one location or platform to facilitate governance and carry out privacy-compliant projects.

Big Data 52

Big Data Coding Project Hadoop 52

phData: Data Engineering

JULY 18, 2023

Why Migrate to a Modern Data Stack? First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse. Central Source of Truth for Analytics A Cloud Data Warehouse (CDW) is a type of database that provides analytical data processing and storage capabilities within a cloud-based infrastructure.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

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

Monte Carlo

AUGUST 19, 2023

By integrating tools from a variety of vendors, a data platform enables a data engineering team to not only manage an organization’s data but also activate it for a domain’s use cases. In today’s data-driven landscape, building a data platform is no longer a nice-to-have, but a necessity for most organizations.

Building 52

Building BI Data Lake Data Governance 52