phData: Data Engineering

SEPTEMBER 19, 2023

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

DECEMBER 28, 2023

CSS is primarily used to polish how HTML documents appear visually. SQL SQL, or Structured Query Language, is one of the top 5 web development languages used for managing and manipulating relational databases. This web development language is frequently used in web development to build, manage, and query databases.

Programming Language 52

Programming Language Java SQL Python 52

Monte Carlo

FEBRUARY 27, 2024

Right now, RAG is the essential technique to make GenAI models useful by giving an LLM access to an integrated, dynamic dataset while responding to prompts. These databases are not just a trend, but a fundamental shift in how data is managed, accessed, and utilized in real-time AI applications.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

Edureka

FEBRUARY 7, 2023

In this case, the service provider creates a managed service that allows users to access these services on demand. For data access, Synapse SQL, an enhanced version of TSQL, is used. ” All types of files, including text files, videos, images, documents, binary data, etc., can be supported by it.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

SEPTEMBER 26, 2023

Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types. Whether your data is structured, like traditional relational databases, or unstructured, such as textual data, images, or log files, Azure Synapse can manage it effectively.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Knowledge Hut

OCTOBER 30, 2023

Data Integration: Assist in integrating data from multiple sources into Power BI, ensuring data consistency and accuracy. Data Validation: Help validate data against predefined business rules and ensure data quality. Ensure compliance with data protection regulations.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Towards Data Science

MARCH 5, 2024

The storage system is using Capacitor, a proprietary columnar storage format by Google for semi-structured data and the file system underneath is Colossus, the distributed file system by Google. This comes with the advantages of reduction of redundancy, data integrity and consequently, less storage usage.

Bytes 67

Bytes Google Cloud Cloud Storage Utilities 67

Edureka

FEBRUARY 8, 2024

Use cases for memory-optimized instances include- Database Servers- Applications like relational databases benefit from the higher memory capacity to store and retrieve data efficiently. In-Memory Caching- Memory-optimized instances are suitable for in-memory caching solutions, enhancing the speed of data access.

AWS 52

AWS NoSQL Deep Learning Datasets 52

Data Engineering Weekly

MARCH 24, 2023

Drawback #1: Not Every Database Supports Transaction The relational database support transaction for multiple mutation statements. However, if you use systems like DynamoDB, the transaction support falls under the application or the Data Access Layer. You can find the source code and the documentation here.

Engineering 67

Engineering Data Transportation Database 67

ProjectPro

NOVEMBER 15, 2021

When any particular project is open-sourced, it makes the source code accessible to anyone. The adaptability and technical superiority of such open-source big data projects make them stand out for community use. DataFrames are used by Spark SQL to accommodate structured and semi-structured data.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Rockset

OCTOBER 20, 2021

This comes on the heels of our latest product releases around more accessible and affordable real-time analytics with Rollups on Streaming Data and Rockset Views. For high velocity data, most commonly coming from data streams, you can roll it up at write-time. S3 or GCS), NoSQL databases (e.g. PostgreSQL or MySQL).

SQL 52

SQL PostgreSQL MongoDB NoSQL 52

Edureka

FEBRUARY 9, 2023

Azure Data Engineers Jobs – The Demand Azure Data Engineer Skills What does an Azure Data Engineer Do? Who is an Azure Data Engineer? Data is an organization’s most valuable asset, so making sure it can be accessed quickly and securely should be a top priority.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

DECEMBER 17, 2021

Industry experts at ProjectPro say that although both have been developed for the same task, i.e., data storage, they vary significantly in terms of the audience they cater to. NoSQL databases are designed to store unstructured data like graphs, documents, etc., whereas SQL databases deal with structured data in tables.

Data Science 52

Data Science SQL NoSQL Programming Language 52

ProjectPro

JANUARY 25, 2022

PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization The PySpark Architecture The PySpark architecture consists of various parts such as Spark Conf, RDDs, Spark Context, Dataframes , etc.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JANUARY 19, 2022

Azure Data Engineer Job Description | Accenture Azure Certified Data Engineer Azure Data Engineer Certification Microsoft Azure Projects for Practice to Enhance Your Portfolio FAQs Who is an Azure Data Engineer? This is where the Azure Data Engineer enters the picture.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

DECEMBER 26, 2023

This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc. As a Data engineer, you need to be quite proficient in SQL and NoSQL.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

MARCH 19, 2015

Relational Databases – The fundamental concept behind databases, namely MySQL, Oracle Express Edition, and MS-SQL that uses SQL, is that they are all Relational Database Management Systems that make use of relations (generally referred to as tables) for storing data.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

JUNE 6, 2015

It also detects any problems that might be there in the data – so there is some data quality layer. There is Master Function Data and Meta Function Data. Then there is the Access layer to bring the reports to the end users. In the data transformation we saw lot of limitation with this kind of BI architecture.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

ProjectPro

JULY 13, 2015

Large commercial banks like JPMorgan have millions of customers but can now operate effectively-thanks to big data analytics leveraged on increasing number of unstructured and structured data sets using the open source framework - Hadoop. It does not help the bank to be responsive to potential investment opportunities.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

NOVEMBER 14, 2015

Data Integration 3.Scalability Specialized Data Analytics 7.Streaming Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization 1. Data Migration RDBMSs were inefficient and failed to manage the growing demand for current data. Scalability 4.Link

Hadoop 52

Hadoop Project Big Data Healthcare 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Netflix Tech

DECEMBER 14, 2018

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve.

Media 94

Media Database Metadata Data Schemas 94

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

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Data warehouse. Traditional data warehouse platform architecture. Key features of a data lakehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

MAY 14, 2021

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

JULY 29, 2022

How HDFS master-slave structure works. A master node called NameNode maintains metadata with critical information, controls user access to the data blocks, makes decisions on replications, and manages slaves. Today, companies have the opportunity to run Big Data analytics on Hadoop without investing in hardware.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

MAY 12, 2023

Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. Unlike structured data, which is organized into neat rows and columns within a database, unstructured data is an unsorted and vast information collection.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

U-Next

SEPTEMBER 29, 2022

What Is a Data-Driven Culture? . Data on a daily basis surround us. As data becomes more accessible, companies are leveraging it to grow and make an impact. The importance of data today cannot be overstated. Having a data-driven culture is essential for organizations’ survival and growth. .

Management 52

Management Unstructured Data Data Government 52