ProjectPro

FEBRUARY 16, 2023

Data Engineers and Data Scientists require efficient methods for managing large databases, which is why centralized data warehouses are in high demand. Cloud computing has made it easier for businesses to move their data to the cloud for better scalability, performance, solid integrations, and affordable pricing.

AWS 52

AWS Data Management ETL Tools Management 52

Knowledge Hut

NOVEMBER 17, 2023

To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. Additionally, they convert data into formats that can be used and store it effectively and securely in the Azure cloud.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Grouparoo

OCTOBER 26, 2021

Origin The origin of a data pipeline refers to the point of entry of data into the pipeline. This includes the different possible sources of data such as application APIs, social media, relational databases, IoT device sensors, and data lakes. Grouparoo, however, offers effective solutions to these challenges.

Data Pipeline 52

Data Pipeline ETL Tools ETL System Data Warehouse 52

DataKitchen

JUNE 12, 2023

We had been talking about “Agile Analytic Operations,” “DevOps for Data Teams,” and “Lean Manufacturing For Data,” but the concept was hard to get across and communicate. I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science.

ETL Tools 52

ETL Tools Data Science Data Lake Hadoop 52

Knowledge Hut

SEPTEMBER 26, 2023

Businesses require an infrastructure that educates their staff to sort and analyze this volume of data to handle such big data. Data engineering services can be used in this situation. Data engineers work on the data to organize and make it usable with the aid of cloud services.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Databand.ai

JULY 5, 2023

They provide insights into the health of data integration processes, detect issues in real-time, and enable teams to optimize data flows. Data lake and data warehouse monitoring: These tools monitor the performance, storage, and access patterns of data lakes and data warehouses, ensuring optimal performance and data availability.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

Data Engineering Weekly

JANUARY 6, 2023

Data quality, data contract, data discovery, compliance, governance, and ETL tools all need metadata–row counts, cardinality, distribution, max, min, number of nulls, and so on. In-tool metadata collection–by far the most common–is inefficient and error prone. Recap is a young project.

Metadata 40

Metadata ETL Tools MySQL Data Lake 40

Knowledge Hut

NOVEMBER 28, 2023

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. This can be easier when you are using existing cloud services.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

FEBRUARY 21, 2023

Vendor-Specific Data Engineering Certifications The vendor-specific data engineer certifications help you enhance your knowledge and skills relevant to specific vendors, such as Azure, Google Cloud Platform, AWS, and other cloud service vendors. Expertise in leveraging cloud platforms, data services, and solutions.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

AUGUST 13, 2021

Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis.

Data Pipeline 107

Data Pipeline Data Lake ETL Tools Unstructured Data 107

AltexSoft

AUGUST 4, 2021

Since data marts provide analytical capabilities for a restricted area of a data warehouse, they offer isolated security and isolated performance. Data mart vs data warehouse vs data lake vs OLAP cube. Data lakes, data warehouses, and data marts are all data repositories of different sizes.

Data Lake 64

Data Lake Data Warehouse ETL Tools Telecommunication 64

Knowledge Hut

NOVEMBER 19, 2023

One of the most important responsibilities for experts in big data is configuring the cloud to store data and provide high availability. As a result, data engineers working with big data today require a basic grasp of cloud computing platforms and tools.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

Knowledge Hut

JULY 6, 2023

IT Professionals looking to work in the cloud domain are expected to have a sound understanding of Azure tools as well as development and monitoring tools. Azure Monitoring Tools: Overview Microsoft Azure is the second-most popular cloud service provider, next to Amazon Web Service. Why are Azure Tools Important?

Amazon Web Services 52

Amazon Web Services Data Lake Java SQL 52

ProjectPro

JANUARY 27, 2023

Over the past few years, data-driven enterprises have succeeded with the Extract Transform Load (ETL) process to promote seamless enterprise data exchange. This indicates the growing use of the ETL process and various ETL tools and techniques across multiple industries.

BI 52

BI ETL Tools Retail Healthcare 52

Edureka

FEBRUARY 9, 2023

Data infrastructure, data warehousing, data mining, data modelling, and other tasks are all part of a company’s data science programme, and data engineers are in charge of the majority of them. Microsoft Azure is a modern cloud platform that provides a wide range of services to businesses.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JANUARY 19, 2022

Data infrastructure, data warehousing, data mining, data modeling, etc., are part of a company's data science program, and data engineers handle most of these tasks. Microsoft Azure is a modern cloud platform that offers businesses a wide range of services.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

OCTOBER 8, 2021

They are applied to retrieve data from the source systems, perform transformations when necessary, and load it into a target system ( data mart , data warehouse, or data lake). So, why is data integration such a big deal? On-premise data integration tools. Cloud-based data integration tools.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

AltexSoft

OCTOBER 30, 2021

Data engineers are programmers first and data specialists next, so they use their coding skills to develop, integrate, and manage tools supporting the data infrastructure: data warehouse, databases, ETL tools, and analytical systems. Providing data access tools. Data warehousing.

Data Engineering 98

Data Engineering Data Engineer Engineering Algorithm 98

Rockset

OCTOBER 11, 2022

Introduction Managing streaming data from a source system, like PostgreSQL, MongoDB or DynamoDB, into a downstream system for real-time analytics is a challenge for many teams. For a system like Elasticsearch , engineers need to have in-depth knowledge of the underlying architecture in order to efficiently ingest streaming data.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Rockset

JANUARY 28, 2022

Wealth of Data, Little Observability Those metrics included the data generated by existing and new Seesaw users as they interacted with the service. Storing all of that data was not a problem. Seesaw was able to scale up its main database, an Amazon DynamoDB cloud-based service optimized for large datasets.

NoSQL 52

NoSQL PostgreSQL MongoDB ETL Tools 52

Edureka

FEBRUARY 7, 2023

To help you get a head start on your preparation, I’ve compiled a list of the Top 30+ Azure Data Engineer Interview Questions. Microsoft Azure is one of the most popular and rapidly expanding cloud service providers. When it comes to professionals, data engineers are the most in-demand in the IT industry.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Databand.ai

JULY 19, 2023

ELT is commonly used in big data projects and real-time processing where speed and scalability are critical. In the past, data was often stored in a single location, such as a database or a data warehouse. This dispersed data environment creates a challenge for businesses that need to access and analyze their data.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Silectis

MARCH 9, 2021

This has been driven by the relatively recent emergence of “data engineering” as an organized discipline, the fact that data engineering is sometimes perceived as unglamorous relative to its cousin, data science, and the high hurdle for new entrants trying to become productive. – Demetri Kotsikopoulos , CEO of Silectis 3.

Data Engineering 52

Data Engineering Data Engineer Engineering ETL Tools 52

Grouparoo

NOVEMBER 16, 2021

Transformation is the process of converting the data into the required standard format. Loading is the process of warehousing the data in an accessible location. The advent of cloud-based solutions has enabled a switch to Extract, Load, and Transform (ELT). featured image via unsplash

Data Mining 52

Data Mining Raw Data ETL Tools Unstructured Data 52

AltexSoft

JANUARY 26, 2022

The development of new tools and the improvement of old ones has led to the transformation of the traditional data roles, simplifying some job aspects and complicating other ones. Companies start hiring that one data guy or gal that wears all the hats — knows the complete data stack from both the engineering and analytics sides.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

ProjectPro

FEBRUARY 18, 2022

Anyone who works with data, whether a programmer, a business analyst, or a database developer, creates ETL pipelines , either directly or indirectly. ETL is a must-have for data-driven businesses. The transition to cloud-based software services and enhanced ETL pipelines can ease data processing for businesses.

Project 52

Project AWS Kafka Healthcare 52

AltexSoft

SEPTEMBER 10, 2021

These systems can be hosted on-premises, in the cloud, and on IoT devices, etc. With the right data integration strategy, companies can consolidate the needed data into a single place and ensure its integrity and quality for better and more reliable insights. Key types of data integration. Uniform data access integration.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

ProjectPro

NOVEMBER 30, 2021

ETL (Extract, Transform, and Load) Pipeline involves data extraction from multiple sources like transaction databases, APIs, or other business systems, transforming it, and loading it into a cloud-hosted database or a cloud data warehouse for deeper analytics and business intelligence.

Process 52

Process Data Pipeline Data Warehouse AWS 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 84

Engineering Raw Data Data Science Scala 84

ProjectPro

JULY 27, 2021

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms. It is difficult to query the required unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Cloudera

JUNE 16, 2022

During a customer workshop, Laila, as a seasoned former DBA, made the following commentary that we often hear from our customers: “Streaming data has little value unless I can easily integrate, join, and mesh those streams with the other data sources that I have in my warehouse, relational databases and data lake.

Kafka 83

Kafka Manufacturing Data Lake SQL 83

Rockset

FEBRUARY 14, 2022

Seesaw’s cloud-native technology constantly generated a wealth of data around how students and teachers used the service. Seesaw built real-time business observability by using Rockset to analyze that data. And with the wealth of customer data and real-time signals available today, most e-tailers are rushing to take advantage.

BI 52

BI Data Warehouse ETL Tools Data Lake 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

Snowflake

JULY 24, 2023

Our legacy cluster database, combined with traditional code and ETL tooling, meant our work was inefficient,” said Riipinen. Our data infrastructure had simply reached the end of its life.” The company also uses external tables to directly access the semi-structured data within Snowflake.

Building 52

Building Engineering Finance Data Lake 52

Cloudera

NOVEMBER 27, 2023

2: The majority of Flink shops are in earlier phases of maturity We talked to numerous developer teams who had migrated workloads from legacy ETL tools, Kafka streams, Spark streaming, or other tools for the efficiency and speed of Flink. Vendors making claims of being faster than Flink should be viewed with suspicion.

Kafka 78

Kafka SQL ETL Tools Data Lake 78

Rockset

FEBRUARY 17, 2022

New Thing 3: Data Empowers Business Team Members Zack Khan, Hightouch In 2022, every modern company now has a cloud data warehouse like Snowflake or BigQuery. Chances are, you’re primarily using it to power dashboards in BI tools. First party data (data explicitly collected from customers) has never been more important.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52