phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. Consistency of data throughout the data lake.

Data Lake 52

Data Lake Process Metadata Data Warehouse 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

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

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

NOVEMBER 2, 2023

Setting Up a Relational Database with Amazon RDS Difficulty Level: Intermediate AWS cloud practitioner applications can create relational databases using the Amazon Relational Database Service (RDS). It helps in evaluating what went well and identifying areas for future improvement.

AWS 52

AWS Coding Cloud Project 52

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

NOVEMBER 23, 2021

The traditional way of data integration involves consolidating disparate data within a single repository — commonly a data warehouse — via the extract, transform, load (ETL) process. You can learn more about how such data pipelines are built in our video about data engineering. Data virtualization use cases.

Process 69

Process Data Lake Metadata Data Warehouse 69

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. If we look at history, the data that was generated earlier was primarily structured and small in its outlook.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 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

FEBRUARY 28, 2024

In this blog, we will explore the future of big data in business, its applications, and the technologies that will drive its evolution. What is Big Data? Big data refers to large amounts of data. The differentiation between data and big data becomes clear once we look at the methods of analyzing them.

Big Data 52

Big Data Cloud Storage Healthcare SQL 52

Knowledge Hut

JANUARY 30, 2024

Whether you're a seasoned data scientist or just stepping into the world of data, come with me as we unravel the secrets of data extraction and learn how it empowers us to unleash the full potential of data. What is data extraction? What is the purpose of extracting data?

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

JUNE 23, 2023

Data engineers make a tangible difference with their presence in top-notch industries, especially in assisting data scientists in machine learning and deep learning. You should have the expertise to collect data, conduct research, create models, and identify patterns.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

ProjectPro

FEBRUARY 8, 2023

In 2023, more than 5140 businesses worldwide have started using AWS Glue as a big data tool. 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. AWS Glue automates several processes as well.

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AWS Scala Metadata Data Lake 98

U-Next

AUGUST 25, 2022

Or, to put it another way, the MongoDB environment provides you with a server that you can launch and use to host several datasets utilizing MongoDB. Due to its NoSQL database, the data is kept as a collection and documents. As a result, the databases, collections, and publications are connected.

MongoDB 40

MongoDB Architecture NoSQL MySQL 40

AltexSoft

AUGUST 29, 2023

Another distinction is the ETL vs. ELT choice: In data warehouses, Extract and Transform processes usually occur before data is loaded into the warehouse. Many organizations also deploy data marts , which are dedicated storage repositories for specific business lines or workgroups. Structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

U-Next

SEPTEMBER 9, 2022

Hadoop can scale up from a single server to thousands of servers and analyze organized and unstructured data. . What is Hadoop in Big Data? . Apache Hadoop is useful for managing and processing large amounts of data in a distributed computing environment. Thus, a highly popular platform in the Big Data world.

Hadoop 40

Hadoop Big Data Management Unstructured Data 40

AltexSoft

MAY 14, 2021

Not only does Big Data apply to the huge volumes of continuously growing data that come in different formats, but it also refers to the range of processes, tools, and approaches used to gain insights from that data. Key Big Data characteristics. Velocity is the speed at which the data is generated and processed.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

DECEMBER 26, 2023

Big Data is an immense amount of data that is constantly growing exponentially. Due to its vastness and complexity, no traditional data management system can adequately store or process this data. The New York Stock Exchange, which generates one terabyte of new trade data each day, is a classic example of big data.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

Knowledge Hut

MARCH 20, 2024

Builds and manages data processing, storage, and management systems. Full-Stack Engineer Front-end and back-end database design are the domains of expertise for full-stack engineers and developers. Determines and corrects complicated problems throughout the software development process.

Software Engineer 52

Software Engineer Software Engineering Engineering Java 52

ProjectPro

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Monte Carlo

JANUARY 24, 2023

This creates a centralized network of all your data, where connections and relationships can be identified freely—without relying on point-to-point integrations between specific applications or datasets. Repetitive tasks get automated, and data that would otherwise sit idle is automatically ingested and put to use.

Metadata 40

Metadata Unstructured Data Data Architecture 40

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. Work closely with software engineers and data scientists. Technical Data Engineer Skills 1.Python

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

AltexSoft

OCTOBER 3, 2022

” Basically, a knowledge graph is obtained in the process of filling ontologies with instances of real data. The basics of knowledge graphs open to users were first implemented in 2007 when the DBpedia knowledge base was created as a result of the semantic processing of Wikipedia article infoboxes. Knowledge graph example.

Relational Database 52

Relational Database Banking Media Computer Science 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 Pipeline-centric Machine Learning 52

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

U-Next

AUGUST 3, 2022

Up until 2010, it was extremely difficult for companies to store data. Now that well-known technologies like Hadoop and others have resolved the storage issue, the emphasis is on information processing. And Data Science has a significant impact here. The people who have inquiries about data are known as Data Scientists.

Retail 52

Retail Data Science Computer Science Entertainment 52

AltexSoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. What is Hadoop?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

DECEMBER 7, 2021

Data Pipeline Tools AWS Data Pipeline Azure Data Pipeline Airflow Data Pipeline Learn to Create a Data Pipeline FAQs on Data Pipeline What is a Data Pipeline? A pipeline may include filtering, normalizing, and data consolidation to provide desired data.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Kicking off a big data analytics project is always the most challenging part.

Big Data 52

Big Data Coding Project Hadoop 52

AltexSoft

FEBRUARY 11, 2023

The daily tasks of a data architect require more of a strategic thinking, while a data engineer’s workload is more about building the software infrastructure, which are technical tasks. By the way, we have a video dedicated to the data engineering working principles. Feel free to enjoy it.

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

MARCH 19, 2015

RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data. As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT

NoSQL 49

NoSQL Big Data SQL Database-centric 49

AltexSoft

NOVEMBER 10, 2021

This enables different teams to use a single system to access all of the enterprise data for a range of projects, including data science, machine learning, and business intelligence. Let’s elaborate on this and figure out how a data lakehouse is different from its ancestors and name inspirers in more detail. Data warehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

FEBRUARY 21, 2023

AWS Certification demonstrates to potential employers that you possess the technical know-how to conduct complex data analytics tasks using fundamental AWS data analytics services like Amazon EMR , Redshift , and QuickSight. The registration fee for the Microsoft Azure Data Engineer Associate DP-203 certification is $165.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

JULY 13, 2015

Apache Hadoop is the framework of choice for JPMorgan - not only to support the exponentially growing data size but more importantly for the fast processing of complex unstructured data. JP Morgan has massive amounts of data on what its customers spend and earn.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

NOVEMBER 14, 2015

With Big Data came a need for programming languages and platforms that could provide fast computing and processing capabilities. Data Integration 3.Scalability Specialized Data Analytics 7.Streaming Owned by Apache Software Foundation, Apache Spark is an open-source data processing framework. Scalability 4.Link

Hadoop 52

Hadoop Project Big Data Healthcare 52