U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Lake? .

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Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? AWS Glue is here to put an end to all your worries! Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4

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AWS Scala Metadata Data Lake 98

Knowledge Hut

NOVEMBER 2, 2023

As an AWS Cloud Practitioner with experience in delivering multiple AWS cloud practitioner projects, I vividly recall assisting a startup to prove the scalability of their AI solution on AWS during one of my early projects. This will pique your interest in using the AWS platform.

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AWS Coding Cloud Project 52

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. Snowflake Unistore consolidates both into a single database so users get a drastically simplified architecture with less data movement and consistent security and governance controls.

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Data Architecture Architecture Data Lake Kafka 79

Knowledge Hut

NOVEMBER 17, 2023

AWS has changed the life of data scientists by making all the data processing, gathering, and retrieving easy. One popular cloud computing service is AWS (Amazon Web Services). Many people are going for Data Science Courses in India to leverage the true power of AWS. What is Amazon Web Services (AWS)?

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AWS Data Science Certification Amazon Web Services 52

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake? What is a Data lake?

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ProjectPro

JANUARY 24, 2023

A survey by Data Warehousing Institute TDWI found that AWS Glue and Azure Data Factory are the most popular cloud ETL tools with 69% and 67% of the survey respondents mentioning that they have been using them. Azure Data Factory and AWS Glue are powerful tools for data engineers who want to perform ETL on Big Data in the Cloud.

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Monte Carlo

JULY 15, 2024

We recently spoke with Killian Farrell , Principal Data Scientist at insurance startup AssuranceIQ to learn how his team built an LLM-based product to structure unstructured data and score customer conversations for developing sales and customer support teams. Read on to find out what they did, and what they learned!

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phData: Data Engineering

NOVEMBER 8, 2024

Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It can also be integrated into major data platforms like Snowflake. Contact phData Today!

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Architecture Systems Data Lake Google Cloud 52

Monte Carlo

MAY 31, 2022

Integrating with it is the holy grail of Spark lineage because it contains all the information needed for how data moves through the data lake and how everything is connected. You can run Spark jobs across solutions like AWS Glue, EMR, and Databricks. That makes the DAG the equivalent of a SQL execution plan.

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Data Lake Building Scala Metadata 52

Monte Carlo

OCTOBER 31, 2024

Key Differences Between AI Data Engineers and Traditional Data Engineers While traditional data engineers and AI data engineers have similar responsibilities, they ultimately differ in where they focus their efforts. Data Storage Solutions As we all know, data can be stored in a variety of ways.

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Data Engineering Data Engineer Engineering Unstructured Data 52

Monte Carlo

JANUARY 16, 2024

In this blog post, we’ll look at six innovations that are shaping the future of the data warehousing, as well as challenges and considerations that organizations should keep in mind. Data lake and data warehouse convergence 2. Easier to stream real-time data 3. Zero-copy data sharing 4.

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Data Lake Data Warehouse Unstructured Data AWS 52

Data Engineering Weekly

MARCH 3, 2024

The migration enhanced data quality, lineage visibility, performance improvements, cost reductions, and better reliability and scalability, setting a robust foundation for future expansions and onboarding. link] Martin Chesbrough: How to Build a Modern Data Team?

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Data Engineering Data Engineer Pipeline-centric Engineering 67

Towards Data Science

DECEMBER 4, 2023

A robust data infrastructure is a must-have to compete in the F1 business. We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Looker, PowerBI, Tableau, ThoughtSpot, …) and data pipelines tools. It depends.

Data Engineering 81

Data Engineering Data Engineer Engineering Data Lake 81

U-Next

MARCH 1, 2023

Let’s discuss some of the key responsibilities of a Data Engineer: Data Engineers are responsible for deploying the solutions they design and build, and they should have a good knowledge of cloud platforms like AWS, Azure, etc. What is a data lake, and how does it differ from a data warehouse?

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Data Engineering Data Engineer Non-relational Database Engineering 75

DareData

JANUARY 30, 2023

Some examples are: Apache Airflow: An open-source data orchestrator that enables users to define, schedule, and monitor workflows. AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS). Some examples include Amazon Redshift, Azure SQL Data Warehouse, and Google BigQuery.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Cloudera

JUNE 9, 2022

From origin through all points of consumption both on-prem and in the cloud, all data flows need to be controlled in a simple, secure, universal, scalable, and cost-effective way. controlling distribution while also allowing the freedom and flexibility to deliver the data to different services is more critical than ever. .

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Data Collection Data Lake Unstructured Data Retail 93

Monte Carlo

JUNE 26, 2023

Over the past decade, Databricks and Apache Spark™ not only revolutionized how organizations store and process their data, but they also expanded what’s possible for data teams by operationalizing data lakes at an unprecedented scale across nearly infinite use cases. billion in 2020 to $17.6

Data Lake 52

Data Lake Metadata Bytes Machine Learning 52

RandomTrees

SEPTEMBER 27, 2024

A valuable feature of One Lake is the ability to create shortcuts that point to other data locations, such as ADLS Gen2 or AWS S3. This eliminates the need to make multiple copies of data assets.

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Database-centric Pipeline-centric IT BI 52

Towards Data Science

FEBRUARY 9, 2024

AWS has been a leader in data streaming, offering templates to establish the outbox pattern and building data streaming products such as MSK , SQS , SNS , Lambdas , DynamoDB and more. Amid the rush to keep up with generative AI and Large Language Model trends, specialized data stores like vector databases become essential.

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Building Transportation Data Lake Metadata 77

Monte Carlo

JUNE 28, 2022

To help organizations realize the full potential of their data lake and lakehouse investments, Monte Carlo, the data observability leader, is proud to announce integrations with Delta Lake and Databricks’ Unity Catalog for full data observability coverage. billion in 2020 to 17.60 billion in 2020 to 17.60

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. They also recently acquired Apache Flink , another streaming solution.

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Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

JUNE 25, 2021

Many Cloudera customers are making the transition from being completely on-prem to cloud by either backing up their data in the cloud, or running multi-functional analytics on CDP Public cloud in AWS or Azure. The Replication Manager service facilitates both disaster recovery and data migration across different environments.

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Cloud Data Lake Cloud Storage Metadata 73

ProjectPro

DECEMBER 7, 2021

The Importance of a Data Pipeline What is an ETL Data Pipeline? What is a Big Data Pipeline? Features of a Data Pipeline Data Pipeline Architecture How to Build an End-to-End Data Pipeline from Scratch? In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

MARCH 28, 2024

Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

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Data Lake ETL Tools Data Warehouse Data Pipeline 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

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.

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Certification Data Engineering Data Engineer Engineering 52

Scott Logic

NOVEMBER 6, 2023

Tech Solutions In this section we think about the variety of technology product categories that we can apply to storing, transferring and analysing data. They’d typically push data they’ve collected into the warehouse system or data lake.

Data Lake 52

Data Lake Kafka BI Unstructured Data 52

Knowledge Hut

SEPTEMBER 26, 2023

Organizations can harness the power of the cloud, easily scaling resources up or down to meet their evolving data processing demands. Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

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

Monte Carlo

AUGUST 31, 2023

Data pipelines can handle both batch and streaming data, and at a high-level, the methods for measuring data quality for either type of asset are much the same. We’ll take a closer look at variables that can impact your data next. Rise of the Data Lakehouse Data warehouse or data lake?

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Monte Carlo

MARCH 28, 2024

In 2021, Vimeo moved from a process involving big complicated ETL pipelines and data warehouse transformations to one focused on data consumer defined schemas and managed self-service analytics. And, of course, experience in data analytics, pipelines, or other forms of data management is vital.

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Engineering Pipeline-centric BI Google Cloud 75

Edureka

FEBRUARY 9, 2023

Some of the top skills to include are: Experience with Azure data storage solutions: Azure Data Engineers should have hands-on experience with various Azure data storage solutions such as Azure Cosmos DB, Azure Data Lake Storage, and Azure Blob Storage.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

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Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

JANUARY 18, 2024

It might not be one of the Data Science service companies, but it is rooted in analyzing user data on every level. For example, Amazon Web Service or AWS is a subsidiary of Amazon, which manages this part of its business and is the largest shareholder in the cloud service industry.

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Data Science Amazon Web Services Big Data Finance 98

Monte Carlo

JANUARY 25, 2023

When it comes to the question of building or buying your data stack, there’s never a one-size-fits-all solution for every data team—or every component of your data stack. The three most popular solutions for data storage and compute include the data warehouse, data lake, and data lakehouse.

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Data Warehouse Building Data Lake Data Storage 40