Knowledge Hut

DECEMBER 21, 2023

NoSQL This database management system has been designed in a way that it can store and handle huge amounts of semi-structured or unstructured data. NoSQL databases can handle node failures. Different databases have different patterns of data storage. Cons : In Avro, the schema is required to read and write data.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Data Engineering Podcast

JUNE 10, 2018

Summary With the increased ease of gaining access to servers in data centers across the world has come the need for supporting globally distributed data storage. Can you describe the architecture of CockroachDB and how it supports distributed ACID transactions?

PostgreSQL 100

PostgreSQL NoSQL Relational Database SQL 100

Knowledge Hut

NOVEMBER 3, 2023

The need for efficient and agile data management products is higher than ever before, given the ongoing landscape of data science changes. MongoDB is a NoSQL database that’s been making rounds in the data science community. What is MongoDB for Data Science? Why Use MongoDB for Data Science?

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Knowledge Hut

JUNE 23, 2023

Go for the best courses for Data Engineering and polish your big data engineer skills to take up the following responsibilities: You should have a systematic approach to creating and working on various data architectures necessary for storing, processing, and analyzing large amounts of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Knowledge Hut

NOVEMBER 28, 2023

As a data engineer description, you must be ready to explore large-scale data processing and use your expertise and soft skills to ensure a scalable and reliable working environment. Data engineers need to work with large amounts of data and maintain the architectures used in various data science projects.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

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. Spatial Database (e.g.-

Database 52

Database NoSQL Telecommunication MongoDB 52

Knowledge Hut

APRIL 23, 2024

Unlike big data warehouse, big data focuses on processing and analyzing data in its raw and unstructured form. It employs technologies such as Apache Hadoop, Apache Spark, and NoSQL databases to handle the immense scale and complexity of big data. What Should You Choose Between Data Warehouse and Big Data?

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

OCTOBER 3, 2023

The task of integrating, manipulating, and merging data from diverse structured and unstructured sources into a structure utilized to build analytics solutions falls within the purview of an Azure Data Engineer, a highly qualified specialist. As a result, they can work on a number of projects and use cases.

Data Engineering 52

Data Engineering Data Engineer Engineering Cloud Computing 52

Knowledge Hut

APRIL 25, 2023

Strong programming skills: Data engineers should have a good grasp of programming languages like Python, Java, or Scala, which are commonly used in data engineering. Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

MARCH 15, 2024

Making decisions in the database space requires deciding between RDBMS (Relational Database Management System) and NoSQL, each of which has unique features. RDBMS uses SQL to organize data into structured tables, whereas NoSQL is more flexible and can handle a wider range of data types because of its dynamic schemas.

NoSQL 52

NoSQL Database-centric Relational Database PostgreSQL 52

Data Engineering Podcast

APRIL 22, 2019

Summary One of the biggest challenges for any business trying to grow and reach customers globally is how to scale their data storage. Can you describe the architecture of FaunaDB and how it has evolved? Can you describe the architecture of FaunaDB and how it has evolved? Can you talk through how it works?

Database 100

Database Cloud NoSQL Scala 100

Data Engineering Podcast

AUGUST 19, 2018

How does the query interface and data storage in DGraph differ from other options? What are your opinions on the graph query languages that have been adopted by other storages systems, such as Gremlin, Cypher, and GSQL? How is DGraph architected and how has that architecture evolved from when it first started?

Database 100

Database PostgreSQL NoSQL Transportation 100

Knowledge Hut

MAY 31, 2023

You’ll also learn about privacy regulations like GDPR (General Data Protection Regulation) and HIPPA (Health Insurance Portability and Accountability Act) that lay down the rules for data privacy and security. Skills required: Cloud platforms, programming languages, and knowledge of microservices architecture.

Cloud Computing 52

Cloud Computing Cloud Programming Language AWS 52

ProjectPro

SEPTEMBER 9, 2021

Hive comparison elaborates on the two tools’ architecture, features, limitations, and key differences. The following is the architecture of Hive. Apache Hive Architecture Apache Hive has a simple architecture with a Hive interface, and it uses HDFS for data storage.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Knowledge Hut

DECEMBER 26, 2023

According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. In other words, they develop, maintain, and test Big Data solutions. To become a Big Data Engineer, knowledge of Algorithms and Distributed Computing is also desirable.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Knowledge Hut

MARCH 19, 2024

As a Data Engineer, you are expected to be familiar with languages like Python, Java, etc. You need to learn about databases such as Apache, Hadoop, or Spark, as well as databases like SQL or NoSQL. The activities involve coming up with the technical direction and architectural framework for software projects.

Software Engineer 52

Software Engineer Software Engineering Engineering Programming Language 52

Knowledge Hut

APRIL 3, 2023

This includes handling data storage, user authentication, and server configuration. This includes topics such as algorithms, data structures, programming languages, and computer architecture. There are several types of databases, including relational, NoSQL, object-oriented, hierarchical, network, and graph databases.

Programming Language 52

Programming Language Computer Science Portfolio PostgreSQL 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Cloud Academy

JANUARY 27, 2022

Part of the Data Engineer’s role is to figure out how to best present huge amounts of different data sets in a way that an analyst, scientist, or product manager can analyze. What does a data engineer do? A data engineer is an engineer who creates solutions from raw data.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

MAY 4, 2023

Salaries for data engineers vary across the globe, depending on various factors such as location, experience, skills and Data Engineer training and certifications taken by the professionals. Data engineering is all about data storage and organizing and optimizing warehouses plus databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Banking 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. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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.

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

ProjectPro

FEBRUARY 25, 2022

Efficient Scheduling and Runtime Increased Adaptability and Scope Faster Analysis and Real-Time Prediction Introduction to the Machine Learning Pipeline Architecture How to Build an End-to-End a Machine Learning Pipeline? The final sample used for training and testing the model is the output of data preprocessing.

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

Rockset

MAY 24, 2021

Serverless architecture entails the dynamic allocation of resources to carry out various execution tasks. In fact, the popularization of separating storage and compute for databases has allowed service providers the ability to offer serverless databases. What Is Serverless? Serverless is not limited to functions.

Database 40

Database Google Cloud AWS Cloud Storage 40

Rockset

JANUARY 23, 2020

While traditional RDBMS databases served well the data storage and data processing needs of the enterprise world from their commercial inception in the late 1970s until the dotcom era, the large amounts of data processed by the new applications—and the speed at which this data needs to be processed—required a new approach.

Database 40

Database MySQL Kafka NoSQL 40

ProjectPro

SEPTEMBER 16, 2021

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies.

NoSQL 52

NoSQL Database Hadoop Big Data 52

Rockset

AUGUST 13, 2019

Low data latency requirements rule out ETL-based solutions which increase your data latency above the real-time threshold and inevitably lead to “ETL hell”. DynamoDB is a fully managed NoSQL database provided by AWS that is optimized for point lookups and small range scans using a partition key.

BI 40

BI NoSQL PostgreSQL AWS 40

Knowledge Hut

JULY 3, 2023

The infrastructure for real-time data ingestion typically consists of several key features: Data Sources: These are the Systems, devices, and applications which create vast amounts of data in real-time. Like IoT devices, sensors, social media platforms, financial data, etc.

Data Ingestion 52

Data Ingestion Pipeline-centric Google Cloud Media 52

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Knowledge Hut

APRIL 25, 2024

Knowledge of Popular Frameworks Backend developers use certain tools to design the architecture of a website. Create data storage and acceptance solutions for websites, especially those that take payments. Utilizing appropriate product lifecycle techniques, such as Agile Scrum and frameworks, create a website architecture.

Programming Language 98

Programming Language Java Algorithm MySQL 98

ProjectPro

MARCH 19, 2015

Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

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? Traditional data warehouse platform architecture. Data lake. Data lake architecture example.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

ProjectPro

JULY 12, 2021

We will now describe the difference between these three different career titles, so you get a better understanding of them: Data Engineer A data engineer is a person who builds architecture for data storage. They can store large amounts of data in data processing systems and convert raw data into a usable format.

Engineering 40

Engineering Deep Learning Software Engineer Software Engineering 40

Knowledge Hut

JULY 31, 2023

Data Storage Fundamental Amazon encourages various data storage solutions like storage, security, and effective data management as part of their AWS basics. Here are some of the ways in which AWS programmers can benefit from these data storage fundamentals.

AWS 52

AWS Amazon Web Services Cloud Computing Consulting 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. Assembles, processes, and stores data via data pipelines that are created and maintained.

Software Engineer 52

Software Engineer Software Engineering Engineering Java 52

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

Database 52

Database NoSQL Management Relational Database 52

ProjectPro

OCTOBER 31, 2016

” The meaning behind asking such real-time or scenario based hadoop interview questions is to test your skills on how you would apply your hadoop skills and approach a given big data problem. Assuming initial data size is 600 TB. How will you estimate the number of data nodes (n)?

Hadoop 52

Hadoop Big Data Utilities NoSQL 52