Knowledge Hut

APRIL 25, 2024

If you pursue the MSc big data technologies course, you will be able to specialize in topics such as Big Data Analytics, Business Analytics, Machine Learning, Hadoop and Spark technologies, Cloud Systems etc. Look for a suitable big data technologies company online to launch your career in the field.

Big Data 98

Big Data Technology NoSQL Hadoop 98

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. The one that people will use for data warehousing includes Apache Impala in it.

Data Warehouse 42

Data Warehouse Relational Database Hadoop BI 42

Rockset

MARCH 26, 2023

Breaking Bad… Data Silos We haven’t quite figured out how to avoid using relational databases. Folks have definitely tried, and while Apache Kafka® has become the standard for event-driven architectures, it still struggles to replace your everyday PostgreSQL database instance in the modern application stack.

Cloud 52

Cloud PostgreSQL Kafka Database 52

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

APRIL 23, 2024

Professionals in database management must ensure that data is appropriately stored, protected, and backed up to prevent data loss and security breaches. Moreover, the growing prominence of big data analytics and cloud computing contributes to the rising demand for database management expertise.

Database 52

Database Management Relational Database SQL 52

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

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

Knowledge Hut

APRIL 23, 2024

Big Data vs Traditional Data The difference between Big Data vs Traditional Data heavily relies on the tools, plans, processes, and objectives used within, which derive useful insights from the datasets. Let us now take a detailed look into how Big Data differs from Traditional relational databases.

Big Data 52

Big Data Relational Database Data Datasets 52

phData: Data Engineering

SEPTEMBER 19, 2023

A rigid data model such as Kimball or Data Vault would ruin this flexibility and essentially transform your data lake into a data warehouse. However, some flexible data modeling techniques can be used to allow for some organization while maintaining the ease of new data additions.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Knowledge Hut

NOVEMBER 17, 2023

Additionally, they convert data into formats that can be used and store it effectively and securely in the Azure cloud. The data engineers are responsible for creating conversational chatbots with the Azure Bot Service and automating metric calculations using the Azure Metrics Advisor.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

NOVEMBER 17, 2023

Amazon Web Services (AWS) delivers on-demand computing resources and facilities in the cloud. It allows developers to configure and secure space online on the server and compute the business on the cloud. So, without further ado, we present to you some of the best AWS products that are available on cloud and how they can be used.

AWS 52

AWS Amazon Web Services PostgreSQL Relational Database 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, 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. But they should!

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, 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. But they should!

Architecture 52

Architecture Data Lake Metadata Unstructured Data 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. Introduction to Designing Data Lakes in AWS.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

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

François Nguyen

MARCH 22, 2021

How can we interoperate between the data domains ? How do we govern all these data products and domains ? It will be illustrated with our technical choices and the services we are using in the Google Cloud Platform. This is really the dark side of the data. It looks nice but it is really not !

Technology 130

Technology Architecture Google Cloud Metadata 130

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

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

AltexSoft

AUGUST 29, 2023

The term data lake itself is metaphorical, evoking an image of a large body of water fed by multiple streams, each bringing new data to be stored and analyzed. Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

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

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

Monte Carlo

MAY 9, 2023

Many, many data teams rely on them every day to power reporting and data products. That’s why we’re excited to announce the Monte Carlo data observability platform now integrates with Postgres , MySQL , and Microsoft SQL Server databases.

MySQL 52

MySQL Database SQL Relational Database 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

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. Destinations can vary depending on the use case of the pipeline.

Data Pipeline 52

Data Pipeline ETL Tools ETL System Data Warehouse 52

AltexSoft

AUGUST 4, 2021

Now let’s think of sweets as the data required for your company’s daily operations. Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit.

Data Lake 64

Data Lake Data Warehouse ETL Tools Telecommunication 64

Knowledge Hut

JUNE 23, 2023

Let us look at the steps to becoming a data engineer: Step 1 - Skills for Data Engineer to be Mastered for Project Management Learn the fundamentals of coding skills, database design, and cloud computing to start your career in data engineering. Pathway 2: How to Become a Certified Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Knowledge Hut

MARCH 20, 2024

They are responsible for establishing and managing data pipelines that make it easier to gather, process, and store large volumes of structured and unstructured data. Helps to ensure data availability, consistency, and integrity by collaborating with different data storage systems.

Software Engineer 52

Software Engineer Software Engineering Engineering Java 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. Actions: Identify the primary goals of your pipeline, such as automating data reporting for monthly sales data.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

Towards Data Science

MARCH 5, 2024

At its core, BigQuery is a serverless Data Warehouse for analytical purposes and built-in features like Machine Learning ( BigQuery ML ). In that case, queries are still processed using the BigQuery compute infrastructure but read data from GCS instead.

Bytes 70

Bytes Google Cloud Cloud Storage Utilities 70

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

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

Cloudera

AUGUST 26, 2020

On August 18, we completed our Enterprise Data Cloud vision of bringing a truly hybrid cloud experience with the general availability of Cloudera Data Platform Private Cloud (CDP Private Cloud). Here’s how our partner ecosystem supports CDP Private Cloud for example. Certified Data Quality Partner.

Machine Learning 82

Machine Learning BI Big Data Data Warehouse 82

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

Data Engineering Podcast

SEPTEMBER 3, 2018

The Skafos platform from Metis Machine was built to give your data scientists the end-to-end support that they need throughout the machine learning lifecycle. Request a demo at dataengineeringpodcast.com/metis-machine to learn more about how Metis Machine is operationalizing data science.

Data Management 100

Data Management Management Relational Database Business Intelligence 100

Knowledge Hut

JANUARY 24, 2024

Supports numerous data sources It connects to and fetches data from a variety of data sources using Tableau and supports a wide range of data sources, including local files, spreadsheets, relational and non-relational databases, data warehouses, big data, and on-cloud data.

BI 98

BI Business Intelligence Non-relational Database Data Analysis 98

AltexSoft

OCTOBER 8, 2021

Data integration defines the process of collecting data from a number of disparate source systems and presenting it in a unified form within a centralized location like a data warehouse. 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

Rockset

FEBRUARY 2, 2022

3 – Use a Data Warehouse Next, you can replicate your data to a data warehouse. The benefit of these tools is that they’re built specifically for data analytics. Data warehouses scale well and are well-suited to BI and advanced analytics use cases.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52