Striim

SEPTEMBER 11, 2024

This method is advantageous when dealing with structured data that requires pre-processing before storage. Conversely, in an ELT-based architecture, data is initially loaded into storage systems such as data lakes in its raw form. Would the data be stored on cloud or on-premises?’

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Cloudera

JUNE 16, 2022

Building real-time data analytics pipelines is a complex problem, and we saw customers struggle using processing frameworks such as Apache Storm, Spark Streaming, and Kafka Streams. . Without context, streaming data is useless.”

Kafka 88

Kafka Manufacturing Data Lake SQL 88

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 Database 64

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

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

APRIL 2, 2018

News on Hadoop - March 2018 Kyvos Insights to Host Session "BI on Big Data - With Instant Response Times" at the Gartner Data and Analytics Summit 2018.PRNewswire.com, Source : [link] ) The data lake continues to grow deeper and wider in the cloud era.Information-age.com, March 5 , 2018.

Hadoop 40

Hadoop Data Lake Relational Database Big Data 40

AltexSoft

NOVEMBER 23, 2021

But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

MAY 2, 2017

Cloudera has shown its excitement and interest in presenting itself as a modern platform for data management , machine learning and advanced data analytics. Source : [link] ) Commonwealth Bank targets SMEs with new big data analytics platform.Zdnet.com, April 4, 2017. Source : [link] ) Data Works, Hadoop 3.0

Hadoop 52

Hadoop Entertainment Data Lake Big Data 52

Knowledge Hut

NOVEMBER 19, 2023

It makes it possible for all companies from all industries to utilize it for a variety of use cases, including data engineering, operational data integration, analytics, integrating data into data warehouses, and more. Obtaining the Data Engineer Azure certification is a great way to learn this important tool.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

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

ProjectPro

APRIL 1, 2016

(Source: [link] ) Hadoop is powering the next generation of Big Data Analytics. NetworkAsia.net Hadoop is emerging as the framework of choice while dealing with big data. Four years ago Centrica was struggling hard on how to deal with the exponential increase in big data. March 11, 2016. March 31, 2016. Computing.co.uk

Hadoop 52

Hadoop BI Big Data Big Data Tools 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. They work with various stakeholders to provide real-time data analytics, maintain data quality and integrity, and deliver insightful data to the business.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

AUGUST 22, 2022

What is data fabric? A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., Data fabric vs data mesh.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. Structured data is modeled to be easily searchable and occupy minimal storage space.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

NOVEMBER 17, 2023

It provides the following functions: Monitor Govern Secure Configure Protect Migrate Data Services Azure data services are a set of managed data-related services like searching, analysis, relational databases, file storage, time-series data, text searching, etc.

Data Lake 52

Data Lake Programming Language Certification Java 52

AltexSoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. ELT allows them to work with the data directly.

Process 52

Process Building Raw Data Data Lake 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

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. 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.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

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

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

Rockset

JULY 6, 2022

Typically stored in SQL statements, the schema also defines all the tables in the database and their relationship to each other. Data lakes built on NoSQL databases such as Hadoop are the best example of scaled-out data repositories of mixed types.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

ProjectPro

JULY 27, 2021

Also, you will find some interesting data engineer interview questions that have been asked in different companies (like Facebook, Amazon, Walmart, etc.) that leverage big data analytics and tools. Preparing for data engineer interviews makes even the bravest of us anxious.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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.

Database 52

Database SQL Process NoSQL 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. Learning SQL is essential to comprehend the database and its structures.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

ProjectPro

NOVEMBER 15, 2021

It incorporates caching, stream computing, message queuing, and other functionalities to decrease the complexity and expenses of development and operations, in addition to the 10x quicker time-series database. DataFrames are used by Spark SQL to accommodate structured and semi-structured data.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

FEBRUARY 21, 2023

This section mainly focuses on the three most valuable and popular vendor-specific data engineering certifications- AWS, Azure , and GCP. AWS Certified Big Data - Specialty An excellent way to advance your career in data engineering is to earn the AWS Certified Big Data – Specialty certification.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

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 Database 42

ProjectPro

JANUARY 31, 2023

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. Get ready to expand your knowledge and take your big data career to the next level! “Data analytics is the future, and the future is NOW!

Big Data 52

Big Data Hadoop Relational Database AWS 52

ProjectPro

NOVEMBER 14, 2015

Apache Hadoop and Apache Spark fulfill this need as is quite evident from the various projects that these two frameworks are getting better at faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Data Migration 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Grouparoo

NOVEMBER 5, 2021

The advantage is that it preserves the integrity of the source data where compliance or security restrictions are necessary. Data warehousing is the centralized storage of integrated data following its cleansing and transformation into a unified dataset.

Data Integration 40

Data Integration Datasets Data Warehouse Big Data 40

Rockset

APRIL 20, 2020

Why Do Data Relationships Matter? We live in a highly connected world where handling data relationships is important. Relational databases are good at handling relationships, but with constantly changing business requirements, the fixed schema of these databases results in scalability and performance issues.

SQL 40

SQL NoSQL Relational Database Database 40

Knowledge Hut

OCTOBER 30, 2023

Develop a long-term vision for Power BI implementation and data analytics. Data Architecture and Design: Lead the design and development of complex data architectures, including data warehouses, data lakes, and data marts. Define data architecture standards and best practices.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

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. Kafka is great for ETL and provides memory buffers that provide process reliability and resilience.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

ProjectPro

JULY 6, 2015

You can click on the link below to listen to a recording of the recent webinar on “Interview Tips to Get Hired by Big Data Hadoop Companies” by Bob Kelly. Big Data Interview Tips The webinar discusses some important tips that candidates can follow to be successful in big data interviews.

Hadoop 40

Hadoop Big Data Recruitment Big Data Skills 40