Snowflake

NOVEMBER 11, 2024

At BUILD 2024, we announced several enhancements and innovations designed to help you build and manage your data architecture on your terms. SnowConvert is an easy-to-use code conversion tool that accelerates legacy relational database management system (RDBMS) migrations to Snowflake. Here’s a closer look.

Data Architecture 59

Data Architecture Architecture Data Lake Kafka 59

DareData

JANUARY 30, 2023

For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production. Examples of relational databases include MySQL or Microsoft SQL Server.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

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

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

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

phData: Data Engineering

NOVEMBER 8, 2024

A data lakehouse integrates the best features of a data lake and a data warehouse, creating a hybrid architecture that can manage structured and unstructured data using open data formats and allows users to access data using any tool. Amazon S3, Azure Data Lake, or Google Cloud Storage).

Architecture 52

Architecture Systems Data Lake Google Cloud 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Structured data is modeled to be easily searchable and occupy minimal storage space.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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

Monte Carlo

MAY 28, 2024

Ensuring all relevant data inputs are accounted for is crucial for a comprehensive ingestion process. Data Extraction : Begin extraction using methods such as API calls or SQL queries. Conversely, stream processing continuously collects data in real-time, enabling immediate analytics.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Edureka

OCTOBER 10, 2024

These include: Azure Services: This is because copying volumes of data from one service to another is very easy with full support for Microsoft Azure Blob Storage, Azure Data Lake Storage Gen 1 and Gen 2, Azure SQL Data Base, and Azure Synapse Analytics. can be ingested in Azure.

MongoDB 40

MongoDB NoSQL Metadata Datasets 40

Knowledge Hut

JUNE 23, 2023

You should have the expertise to collect data, conduct research, create models, and identify patterns. You should be well-versed with SQL Server, Oracle DB, MySQL, Excel, or any other data storing or processing software. You must develop predictive models to help industries and businesses make data-driven decisions.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Rockset

APRIL 20, 2020

It automatically builds indexes that are optimized not just for search but also aggregations and joins, making it fast and easy for your applications to query data, regardless of where it comes from and what format it is in. But this post is about highlighting some workarounds, in case you really want to do SQL-style joins in Elasticsearch.

SQL 40

SQL NoSQL Relational Database Database 40

Rockset

JUNE 7, 2022

Editor Databases are a key architectural component of many applications and services. Traditionally, organizations have chosen relational databases like SQL Server, Oracle , MySQL and Postgres. Relational databases use tables and structured languages to store data.

MongoDB 52

MongoDB NoSQL Relational Database Non-relational Database 52

Rockset

NOVEMBER 1, 2018

As Peter Bailis put it in his post , querying unstructured data using SQL is a painful process. Moreover, developers frequently prefer dynamic programming languages, so interacting with the strict type system of SQL is a barrier. We at Rockset have built the first schemaless SQL data platform.

SQL 40

SQL NoSQL Programming Language Bytes 40

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 Relational Database AWS 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineers are engineers responsible for uncovering trends in data sets and building algorithms and data pipelines to make raw data beneficial for the organization. This job requires a handful of skills, starting from a strong foundation of SQL and programming languages like Python , Java , etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

U-Next

AUGUST 25, 2022

A fully accessible documentation store called MongoDB allows us to interact with data extremely effectively while storing a lot of it. Since MongoDB does not store or retrieve data in the form of columns, it is referred to as a NoSQL (Not Just SQL) database. Is MongoDB A Relational Database?

MongoDB 40

MongoDB Architecture NoSQL MySQL 40

Workfall

MARCH 21, 2023

It is highly available, scalable, and distributed, and it supports: SQL querying from client devices GraphQL ACID transactions WebSocket connections Both structured and unstructured data Graph querying Full-text indexing Geospatial querying Row permission-based access SurrealQL is an out-of-the-box SQL-style query language included with SurrealDB.

PostgreSQL 68

PostgreSQL NoSQL Database Unstructured Data 68

AltexSoft

JUNE 7, 2021

MapReduce performs batch processing only and doesn’t fit time-sensitive data or real-time analytics jobs. Data engineers who previously worked only with relational database management systems and SQL queries need training to take advantage of Hadoop. Cassandra excels at streaming data analysis.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

SEPTEMBER 26, 2023

We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. The main exam for the Azure data engineer path is DP 203 learning path.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

MAY 31, 2023

Some of the most important lists of database project examples using MySQL are: Online Job Portal using Python and SQL database An online job portal is a platform that connects job seekers with potential employers. Here is a link to source codes for Online Job Portal using Python and SQL databases.

Database 52

Database Coding MongoDB Project 52

Striim

SEPTEMBER 11, 2024

It typically includes large data repositories designed to handle varying types of data efficiently. Data Warehouses: These are optimized for storing structured data, often organized in relational databases. It offers scalable and high-performance tools that enable efficient data access and utilization.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

NOVEMBER 28, 2023

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? SQL Today, more and more cloud-based systems add SQL-like interfaces that allow you to use SQL.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Monte Carlo

NOVEMBER 6, 2023

OneTrust Image credit: OneTrust OneTrust’s Data Discovery tool emphasizes understanding and controlling the lifecycle of sensitive data. It offers AI-powered data discovery across structured and unstructured data, allowing businesses to tag data with regulatory context and monitor it over time.

Metadata 40

Metadata Unstructured Data Government Data Governance 40

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. Avro and Parquet File Formats Avro and Parquet are file formats commonly used in data lakes.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

AltexSoft

DECEMBER 23, 2022

In ETL, all the transformations are done before the data is loaded into a destination system. For example, Online Analytical Processing (OLAP) systems only allow relational data structures so the data has to be reshaped into the SQL-readable format beforehand. Map out data loading strategy. Scalability.

Process 52

Process Building Raw Data Data Lake 52

Knowledge Hut

JANUARY 30, 2024

Structured Data: Structured data sources, such as databases and spreadsheets, often require extraction to consolidate, transform, and make them suitable for analysis. This can involve SQL queries or ETL (Extract, Transform, Load) processes. What is SQL data extraction?

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 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

U-Next

SEPTEMBER 9, 2022

The platform distributes Hadoop large data and analytics operations among computer cluster nodes, breaking them down into smaller workloads that may be handled in parallel. Hadoop can scale up from a single server to thousands of servers and analyze organized and unstructured data. . What is Hadoop in Big Data? .

Hadoop 40

Hadoop Big Data Management Unstructured Data 40

Edureka

FEBRUARY 9, 2023

Data Ingestion and Transformation: Candidates should have experience with data ingestion techniques, such as bulk and incremental loading, as well as experience with data transformation using Azure Data Factory. SQL is also an essential skill for Azure Data Engineers.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Data pipelines can be automated and maintained so that consumers of the data always have reliable data to work with.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

SEPTEMBER 22, 2023

Data Engineers On-site and cloud data platform technologies are configured and provisioned by data engineers. They control and protect the flow of both organised and unstructured data coming from various sources. This exam tests how well you can configure each component of a data processing pipeline and set it up.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 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. The “NoSQL” part here stands for “Non-SQL” and “Not Only SQL”.

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

FEBRUARY 8, 2023

This serverless data integration service can automatically and quickly discover structured or unstructured enterprise data when stored in data lakes in Amazon S3, data warehouses in Amazon Redshift, and other databases that are a component of the Amazon Relational Database Service.

AWS 98

AWS Scala Metadata Data Lake 98