Knowledge Hut

NOVEMBER 2, 2023

As an AWS Cloud Practitioner with experience in delivering multiple AWS cloud practitioner projects, I vividly recall assisting a startup to prove the scalability of their AI solution on AWS during one of my early projects. This experience ignited my passion for architecting cost-effective, scalable solutions on the AWS platform.

AWS 52

AWS Coding Cloud Project 52

Towards Data Science

JANUARY 16, 2024

But in order to justify why this concept came into existence, I thought it’d be great to look back in time and understand the evolution of the data landscape. Evolution of the data landscape 1980s — Inception Relational databases came into existence. Organizations began to use relational databases for ‘everything’.

Data Warehouse 66

Data Warehouse Data Architecture Relational Database NoSQL 66

U-Next

MARCH 1, 2023

Introduction Data Engineer is responsible for managing the flow of data to be used to make better business decisions. A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. What is AWS Kinesis?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Monte Carlo

MAY 28, 2024

Data Transformation : Clean, format, and convert extracted data to ensure consistency and usability for both batch and real-time processing. Data Loading : Load transformed data into the target system, such as a data warehouse or data lake.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Knowledge Hut

MARCH 19, 2024

AWS is the gold standard of Cloud Computing and has some reasons for it. market share, while all of its rivals combined, Microsoft Azure (29.4%), Google Cloud (3.0%), and IBM (2.6%), do not even reach that percentage. That shows how much AWS has to offer, and you must know about it if you’re a cloud computing enthusiast.

AWS 52

AWS Cloud Computing Amazon Web Services Relational Database 52

Precisely

JANUARY 25, 2024

But today’s cloud platforms offer similar capabilities, with the added benefits of flexibility, elasticity, and virtually unlimited scalability. The cloud helps companies lower their capital expenditures, enhance operational efficiency, and innovate faster. They’re also valued for their rock-solid reliability, boasting 99.999% uptime.

Metadata 67

Metadata Data Governance Relational Database Government 67

François Nguyen

MARCH 22, 2021

It will be illustrated with our technical choices and the services we are using in the Google Cloud Platform. With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services.

Technology 130

Technology Architecture Google Cloud Metadata 130

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 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

DareData

JANUARY 30, 2023

AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS). Talend Data Fabric: A comprehensive data management platform that includes a range of tools for data integration, data quality, and data governance. Examples of NoSQL databases include MongoDB or Cassandra.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure, also known as Azure, is a well-known cloud computing service offered by Microsoft. It offers a wide range of services, including computing, storage, databases, machine learning, and analytics, making it a versatile choice for businesses looking to harness the power of the cloud. What is Azure Synapse?

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 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

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

NOVEMBER 17, 2023

Today, the Microsoft Azure Administrator AZ-104 is one of the most sought-after certifications for aspiring cloud professionals. It validates an individual’s proficiency in managing cloud services like networking, storage, computing, and security. Develop, test, and deploy applications on the cloud.

Data Lake 52

Data Lake Programming Language Certification Java 52

ProjectPro

FEBRUARY 8, 2023

For e.g., Finaccel, a leading tech company in Indonesia, leverages AWS Glue to easily load, process, and transform their enterprise data for further processing. Another leading European company, Claranet, has adopted Glue to migrate their data load from their existing on-premise solution to the cloud. How Does AWS Glue Work?

AWS 98

AWS Scala Metadata Data Lake 98

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

Data Engineering Podcast

MARCH 13, 2022

If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription RudderStack helps you build a customer data platform on your warehouse or data lake. TimescaleDB, from your friends at Timescale, is the leading open-source relational database with support for time-series data.

Data Lake 100

Data Lake Relational Database Data Data Engineering 100

Rockset

OCTOBER 11, 2022

Elasticsearch was designed for log analytics where data is not frequently changing, posing additional challenges when dealing with transactional data. Rockset, on the other hand, is a cloud-native database, removing a lot of the tooling and overhead required to get data into the system.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

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

AUGUST 22, 2022

According to Flexera’s 2022 State of the Cloud Report , 89 percent of respondents have a multi-cloud strategy with 80 percent having a hybrid cloud approach in place. Organizations have data stored in public and private clouds, as well as in various on-premises data repositories. What is data fabric?

Architecture 52

Architecture Metadata Data Lake Machine Learning 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

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

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 86

Kafka Manufacturing Data Lake SQL 86

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

AltexSoft

DECEMBER 23, 2022

It is a data integration process with which you first extract raw information (in its original formats) from various sources and load it straight into a central repository such as a cloud data warehouse , a data lake , or a data lakehouse where you transform it into suitable formats for further analysis and reporting.

Process 52

Process Building Raw Data Data Lake 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

Grouparoo

OCTOBER 6, 2021

36 Give Data Products a Frontend with Latent Documentation Document more to help everyone 37 How Data Pipelines Evolve Build ELT at mid-range and move to data lakes when you need scale 38 How to Build Your Data Platform like a Product PM your data with business. Increase visibility.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

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 to Ask: What storage solutions (data warehouses, data lakes, etc.)

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 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.

Database 52

Database SQL Process NoSQL 52

AltexSoft

NOVEMBER 23, 2021

Nowadays, all organizations need real-time data to make instant business decisions and bring value to their customers faster. 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. Popular data virtualization tools.

Process 69

Process Data Lake Metadata Data Warehouse 69

Databand.ai

AUGUST 30, 2023

They include the various databases, applications, APIs, and external systems from which data is collected and ingested. Data sources can be structured or unstructured, and they can reside either on-premises or in the cloud.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 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.

Data Pipeline 52

Data Pipeline ETL Tools ETL System Data Warehouse 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

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 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

Silectis

JANUARY 3, 2021

Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse. Cassandra A database built by the Apache Foundation.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40