Silectis

JANUARY 3, 2021

Data Ingestion The process by which data is moved from one or more sources into a storage destination where it can be put into a data pipeline and transformed for later analysis or modeling. Data Integration Combining data from various, disparate sources into one unified view.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

NOVEMBER 28, 2023

ETL is central to getting your data where you need it. Relational database management systems (RDBMS) remain the key to data discovery and reporting, regardless of their location. The data storage platform you choose should be optimized to work effectively within your organization's budget constraints.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

OCTOBER 3, 2023

Further proficiency in visualizing data, analyzing data by using Transact-SQL (T-SQL), and querying relational databases will come handy. Azure Data Engineer Associate Certification (DP-203) DP-300 certification focuses on data solutions on Azure. Prior professional experience with Azure is recommended.

Certification 52

Certification Cloud Computing Machine Learning SQL 52

Rockset

MAY 24, 2021

Serverless Data Tools Myriad tools exist for serverless data storage layers, each one offering its own set of advantages. The most popular data storage layers for a serverless stack include: Amazon S3: Amazon Simple Storage Service is offered through AWS as a scalable infrastructure solution.

Database 40

Database Google Cloud AWS Cloud Storage 40

Knowledge Hut

SEPTEMBER 29, 2023

The latest Azure exam from Microsoft is structured as follows: Design and implement data storage: Creating and implementing a storage structure, a partition, and a serving layer are tested in this portion (40–45%). You can browse the data lake files with the interactive training material.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

FEBRUARY 21, 2023

Knowledge of the definition and architecture of AWS Big Data services and their function in the data engineering lifecycle, including data collection and ingestion, data analytics, data storage, data warehousing, data processing, and data visualization.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

APRIL 1, 2016

NetworkAsia.net Hadoop is emerging as the framework of choice while dealing with big data. It can no longer be classified as a specialized skill, rather it has to become the enterprise data hub of choice and relational database to deliver on its promise of being the go to technology for Big Data Analytics.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

Knowledge Hut

SEPTEMBER 26, 2023

Whether your data is structured, like traditional relational databases, or unstructured, such as textual data, images, or log files, Azure Synapse can manage it effectively. This is particularly valuable in today's data landscape, where information comes in various shapes and sizes.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 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

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 a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Precisely

JANUARY 25, 2024

Today’s cloud systems excel at high-volume data storage, powerful analytics, AI, and software & systems development. Cloud-based DevOps provides a modern, agile environment for developing and maintaining applications and services that interact with the organization’s mainframe data.

Metadata 69

Metadata Data Governance Relational Database Government 69

Knowledge Hut

NOVEMBER 17, 2023

Azure Storage As the name suggests, Azure storage deals with data storage solutions on the Microsoft cloud. It is highly secure and scalable and can be used to store a variety of data objects. They can also use Azure CLI or Azure PowerShell for configuring tasks and data management.

Data Lake 52

Data Lake Programming Language Certification Java 52

ProjectPro

JANUARY 19, 2022

Here are some role-specific skills you should consider to become an Azure data engineer- Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Different methods are used to store different types of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Data Engineering Podcast

FEBRUARY 27, 2022

If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription TimescaleDB, from your friends at Timescale, is the leading open-source relational database with support for time-series data. Time-series data is time stamped so you can measure how a system is changing.

Designing 100

Designing Metadata Data Lake Relational Database 100

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Knowledge Hut

NOVEMBER 19, 2023

As a result, data engineers working with big data today require a basic grasp of cloud computing platforms and tools. Businesses can employ internal, public, or hybrid clouds depending on their data storage needs, including AWS, Azure, GCP, and other well-known cloud computing platforms.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

ProjectPro

FEBRUARY 8, 2023

It offers a simple and efficient solution for data processing in organizations. It offers users a data integration tool that organizes data from many sources, formats it, and stores it in a single repository, such as data lakes, data warehouses, etc., where it can be used to facilitate business decisions.

AWS 98

AWS Scala Metadata Data Lake 98

Edureka

FEBRUARY 9, 2023

Here are some role-specific skills to consider if you want to become an Azure data engineer: Programming languages are used in the majority of data storage and processing systems. Data engineers must be well-versed in programming languages such as Python, Java, and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Knowledge Hut

JULY 24, 2023

According to recent studies, the global database market will grow from USD 63.4 SQL is a powerful tool for managing and manipulating relational databases, and it continues to be widely used in the industry today. One of its most significant benefits is its ability to quickly process a vast amount of data.

SQL 52

SQL Database Process NoSQL 52

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. The difference between data warehouses, lakes, and marts.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Edureka

FEBRUARY 7, 2023

One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure Data Lake Store. It does away with the requirement to import data from an outside source. Export information to Azure Data Lake Store, Azure Blob Storage, or Hadoop.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

NOVEMBER 15, 2021

DataFrames are used by Spark SQL to accommodate structured and semi-structured data. You can also access data through non-relational databases such as Apache Cassandra, Apache HBase, Apache Hive, and others like the Hadoop Distributed File System. Calcite has chosen to stay out of the data storage and processing business.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JULY 27, 2021

Below are some big data interview questions for data engineers based on the fundamental concepts of big data, such as data modeling, data analysis , data migration, data processing architecture, data storage, big data analytics, etc. What is meant by Aggregate Functions in SQL?

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

SEPTEMBER 10, 2021

Consisting of the same steps as in ETL, ELT changes the sequence — it first extracts raw data from sources and loads it into a target source, where transformation happens as and when required. The target system for ELT is usually a data lake or cloud data warehouse. Key types of data integration.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. And most of this data has to be handled in real-time or near real-time.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Cloudera

DECEMBER 12, 2018

I would like to start off by asking you to tell us about your background and what kicked off your 20-year career in relational database technology? Greg Rahn: I first got introduced to SQL relational database systems while I was in undergrad. Greg Rahn: I refer to this as friction-free data landing. you name it.

Data Warehouse 42

Data Warehouse Relational Database Hadoop BI 42

AltexSoft

MAY 12, 2023

Structured data is formatted in tables, rows, and columns, following a well-defined, fixed schema with specific data types, relationships, and rules. A fixed schema means the structure and organization of the data are predetermined and consistent. Without a fixed schema, the data can vary in structure and organization.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

MARCH 14, 2023

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Rockset

FEBRUARY 17, 2022

But our goal is not purely to move data from point A to point B, although that’s how I describe my job to most people. Our end goal is to create some form of a reliable, centralized, and easy-to-use data storage layer that can then be utilized by multiple teams.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52