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 Engineer 52

Data Engineer Data Engineering NoSQL Engineering 52

Hevo

MAY 3, 2024

PostgreSQL, also known as Postgres, is an advanced object-relational database management system (ORDBMS) used for data storage, retrieval, and management. It is available on the Azure platform in a PaaS model (Platform as a Service) through the Azure Database for PostgreSQL service.

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PostgreSQL Relational Database Data Storage Database 40

Knowledge Hut

MARCH 12, 2024

In this article, I will examine the principal distinctions and similarities between SQL vs SQLite databases. Relational databases can be interacted with using this computer language. Data kept in relational databases is managed using the programming language SQL. High data integrity and scalability.

SQL 52

SQL Relational Database PostgreSQL MySQL 52

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Though basic and easy to use, traditional table storage formats struggle to keep up. Track data files within the table along with their column statistics. Contact phData Today!

Architecture 52

Architecture Systems Data Lake Google Cloud 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

Precisely

JANUARY 25, 2024

Today’s cloud systems excel at high-volume data storage, powerful analytics, AI, and software & systems development. It frequently also means moving operational data from native mainframe databases to modern relational databases. Let’s examine each of these patterns in greater detail. Best Practice 2.

Metadata 69

Metadata Relational Database Data Governance Government 69

Knowledge Hut

APRIL 23, 2024

It is designed to support business intelligence (BI) and reporting activities, providing a consolidated and consistent view of enterprise data. Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Hevo

MAY 10, 2024

In today’s data-rich world, businesses must select the right data storage and analysis platform. For many, Heroku PostgreSQL has long been a trusted solution, offering a reliable relational database service in the cloud.

PostgreSQL 40

PostgreSQL Relational Database Data Storage Cloud 40

Databand.ai

AUGUST 30, 2023

DataOps Architecture Legacy data architectures, which have been widely used for decades, are often characterized by their rigidity and complexity. These systems typically consist of siloed data storage and processing environments, with manual processes and limited collaboration between teams.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Knowledge Hut

JULY 24, 2023

It allows changes to be made at various levels of a database system without causing disruptions or requiring extensive modifications to the applications that rely on the data. What is Data Independence of DBMS? But why do we need data integrity in a DBMS?

Database Design 52

Database Design Relational Database Metadata Database 52

Striim

SEPTEMBER 11, 2024

Striim, for instance, facilitates the seamless integration of real-time streaming data from various sources, ensuring that it is continuously captured and delivered to big data storage targets. Data storage Data storage follows.

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Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

JULY 26, 2023

It also has strong querying capabilities, including a large number of operators and indexes that allow for quick data retrieval and analysis. Database Software- Other NoSQL: NoSQL databases cover a variety of database software that differs from typical relational databases. Columnar Database (e.g.-

Database 52

Database NoSQL Telecommunication MongoDB 52

Knowledge Hut

NOVEMBER 17, 2023

Understanding SQL You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer. To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 52

Knowledge Hut

JUNE 30, 2023

DBMS plays a very crucial role in today’s modern information systems, serving as a base for a plethora of applications ranging from some simple record-keeping applications to complex data analysis programs. What is Database Management System? The data dictionary provides multiple benefits to its users and the administrators.

MySQL 52

MySQL Medical Relational Database Database 52

phData: Data Engineering

SEPTEMBER 19, 2023

This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake? What are Data Modeling Methodologies, and Why Are They Important for a Data Lake?

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Data Lake Process Metadata Data Warehouse 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 Engineer 52

Data Engineer Data Engineering Engineering PostgreSQL 52

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

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AWS Scala Metadata Data Lake 98

AltexSoft

SEPTEMBER 23, 2021

A data hub is a central mediation point between various data sources and data consumers. It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. An ETL approach in the DW is considered slow, as it ships data in portions (batches.)

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. This starts at the data source. Data lineage also enables a data team to track the provenance and transformation of data to understand how it has evolved.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. This starts at the data source. Data lineage also enables a data team to track the provenance and transformation of data to understand how it has evolved.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 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

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 Engineer 40

Data Engineer Data Engineering 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 Relational Database AWS 52

Grouparoo

NOVEMBER 29, 2021

The structure of databases tends to depend on each vendor's proprietary implementation, though for data processing, the database's internal structure typically has a limited impact on processing functions.

Raw Data 40

Raw Data Big Data Relational Database Data Warehouse 40

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.

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Big Data Data Analytics IT NoSQL 78

Ascend.io

JANUARY 2, 2024

Ingestion Points at the Source The journey of a data pipeline begins at its sources – or more technically, at the ingestion points. These are the interfaces where the pipeline taps into various systems to acquire data. Questions about the pipeline’s efficiency in terms of resource and cost utilization.

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Data Pipeline Building Raw Data Data Warehouse 52

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

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.

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Data Warehouse Database-centric Metadata Cloud 80

AltexSoft

NOVEMBER 10, 2021

Prior to the recent advances in data management technologies, there were two main types of data stores companies could make use of, namely data warehouses and data lakes. Data warehouse. Another type of data storage — a data lake — tried to address these and other issues. Data lake.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Knowledge Hut

JUNE 20, 2023

Here are 3 ways in which these two technologies are being combined to create powerful new solutions: Immutable Databases: By leveraging blockchain technology, it’s possible to create databases to be immutable. Once data has been added to such a database, it cannot be modified or deleted.

Database 52

Database Java Education Data Collection 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

APRIL 1, 2016

eWeek.com Syncsort has made it easy for mainframe data to work in Hadoop and Spark by upgrading its DMX-h data integration software. Syncsort has delivered this because some of the companies in industries like financial services, banking, and insurance needed to maintain their mainframe data in native format.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

Edureka

FEBRUARY 7, 2023

The main advantage of Azure Files over Azure Blobs is that it allows for folder-based data organisation and is SMB compliant, allowing for use as a file share. Storage for Azure VMs is provided by Azure Disks (Virtual Machines). 13) Examine the capabilities of Azure storage explorer. 15) What is Azure table storage, exactly?

Data Engineer 52

Data Engineer Data Engineering Engineering Hadoop 52

AltexSoft

AUGUST 4, 2021

Modern cloud warehouses make it possible to store data in its raw formats similarly to data lakes. A data mart is a subject-oriented relational database commonly containing a subset of DW data that is specific for a particular business department of an enterprise, e.g., a marketing department.

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Data Lake Data Warehouse ETL Tools Database 64

Knowledge Hut

SEPTEMBER 6, 2023

This is an entry-level database certification, and it is a stepping stone for other role-based data-focused certifications, like Azure Data Engineer Associate, Azure Database Administrator Associate, Azure Developer Associate, or Power BI Data Analyst Associate. Skills acquired : Core data concepts.

Database 52

Database Certification MongoDB MySQL 52

ProjectPro

JULY 30, 2021

There are many cloud computing job roles like Cloud Consultant, Cloud reliability engineer, cloud security engineer, cloud infrastructure engineer, cloud architect, data science engineer that one can make a career transition to. PaaS packages the platform for development and testing along with data, storage, and computing capability.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

AUGUST 11, 2021

Any inconsistencies found in the data are removed, and all gaps that can be filled are filled to ensure that the data maintains integrity. Data Warehouse Layer: Once the data is transformed into the required format, it is saved into a central repository.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52