Data Science Blog: Data Engineering

DECEMBER 23, 2022

Noch konkreter wird der Bedarf an Datenbeschaffung und -aufbereitung in der Business Intelligence, denn diese benötigt für nachhaltiges Reporting feste Strukturen wie etwa ein Data Warehouse. Abbildung 1 – Data Engineering ist der Mittelpunkt einer jeden Datenplattform.

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Towards Data Science

DECEMBER 15, 2023

Taking a hard look at data privacy puts our habits and choices in a different context, however. Data scientists’ instincts and desires often work in tension with the needs of data privacy and security. Anyone who’s fought to get access to a database or data warehouse in order to build a model can relate.

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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?

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Data Engineering Podcast

FEBRUARY 18, 2024

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started.

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Data Lake High Quality Data Data Warehouse Google Cloud 262

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

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Data Pipeline Architecture Kafka AWS 52

Rockset

AUGUST 4, 2021

Organizations that depend on data for their success and survival need robust, scalable data architecture, typically employing a data warehouse for analytics needs. Snowflake is often their cloud-native data warehouse of choice. Snowflake provides a couple of ways to load data.

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ProjectPro

OCTOBER 6, 2021

With 67 zones, 140 edge locations, over 90 services, and 940163 organizations using GCP across 200 countries - GCP is slowly garnering the attention of cloud users in the market. Google Cloud Platform is an online vendor of multiple cloud services which can be used publicly. Beginner Level GCP Sample Projects Ideas 1.

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Google Cloud Project Data Lake Healthcare 52

Monte Carlo

AUGUST 25, 2023

At the same time, 81% of IT leaders say their C-suite has mandated no additional spending or a reduction of cloud costs. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. But, the options for data storage are evolving quickly. Let’s dive in.

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Cloudera

FEBRUARY 16, 2022

Each workspace is associated with a collection of cloud resources. In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage.

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Machine Learning Algorithm Government Metadata 81

Knowledge Hut

JUNE 26, 2023

Hundreds of datasets are available from these two cloud services, so you may practise your analytical skills without having to scrape data from an API. Source: Use Stack Overflow Data for Analytic Purposes 4. We can clean the data, convert the data, and aggregate the data using dbt so that it is ready for analysis.

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Rockset

MAY 24, 2021

Serverless computing (often just called "serverless") is a model where a cloud provider, like AWS, abstracts away the concept of servers from the user. In fact, the popularization of separating storage and compute for databases has allowed service providers the ability to offer serverless databases. What Is Serverless?

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Database Google Cloud AWS Cloud Storage 40

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

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Data Architect Certification Generalist Big Data 87

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Essentially, this is the difference between a lake and a warehouse. On the other hand, a data warehouse contains historical data that has been cleaned and arranged. .

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Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Cloudera

SEPTEMBER 10, 2021

Shared Data Experience ( SDX ) on Cloudera Data Platform ( CDP ) enables centralized data access control and audit for workloads in the Enterprise Data Cloud. The public cloud (CDP-PC) editions default to using cloud storage (S3 for AWS, ADLS-gen2 for Azure).

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ProjectPro

FEBRUARY 16, 2023

Businesses will be better able to make smart decisions and achieve a competitive advantage if they can successfully integrate data from various sources using SQL. If your database is cloud-based, using SQL to clean data is far more effective than scripting languages. But how does SQL play a vital role here?

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Towards Data Science

APRIL 26, 2023

An open-source implementation of a Data Lake with DuckDB and AWS Lambdas A duck in the cloud. Photo by László Glatz on Unsplash In this post we will show how to build a simple end-to-end application in the cloud on a serverless infrastructure. The cloud is better. How big a machine do we need?

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Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Of course you don’t want to re-create the risks and costs of data silos your organization has spent the last decade trying to eliminate.

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Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure, also known as Azure, is a well-known cloud computing service offered by Microsoft. It offers a wide range of services, including computing, storage, databases, machine learning, and analytics, making it a versatile choice for businesses looking to harness the power of the cloud. What is Azure Synapse?

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DareData

JANUARY 30, 2023

AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS). Talend Data Fabric: A comprehensive data management platform that includes a range of tools for data integration, data quality, and data governance. Introduction to Designing Data Lakes in AWS.

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Edureka

FEBRUARY 9, 2023

Data infrastructure, data warehousing, data mining, data modelling, and other tasks are all part of a company’s data science programme, and data engineers are in charge of the majority of them. Microsoft Azure is a modern cloud platform that provides a wide range of services to businesses.

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Ascend.io

MAY 18, 2023

What we think of as “the modern data stack” today is an evolution of the traditional data stack that can be traced back to physical servers that companies kept on-prem, collecting and storing data that would drive innovation over decades. While this on-prem stack of tools worked, it wasn’t ideal.

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ProjectPro

AUGUST 24, 2021

Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis. Data Analytics: A data engineer works with different teams who will leverage that data for business solutions.

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ProjectPro

JANUARY 24, 2023

With the global cloud data warehousing market likely to be worth $10.42 billion by 2026, cloud data warehousing is now more critical than ever. Cloud data warehouses offer significant benefits to organizations, including faster real-time insights, higher scalability, and lower overhead expenses.

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ProjectPro

JANUARY 19, 2022

Data infrastructure, data warehousing, data mining, data modeling, etc., are part of a company's data science program, and data engineers handle most of these tasks. Microsoft Azure is a modern cloud platform that offers businesses a wide range of services.

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Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. Clouds (source: Pexels ). Many of us are all too familiar with the traditional way enterprises operate when it comes to on-premises data warehousing and data marts: the enterprise data warehouse (EDW) is often the center of the universe.

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Cloud BI Cloud Storage Business Intelligence 42

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

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Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

NOVEMBER 30, 2021

In extract-transform-load (ETL), data is obtained from multiple sources, transformed, and stored in a single data warehouse, with access to data analysts , data scientists , and business analysts for data visualization and statistical analysis model building, forecasting, etc.

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AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. There are several widely used unstructured data storage solutions such as data lakes (e.g., Hadoop, Apache Spark).

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AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

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Scala Data Lake BI Google Cloud 64

Monte Carlo

AUGUST 19, 2023

With companies moving their data platforms to the cloud, the emergence of cloud-native solutions ( data warehouse vs data lake or even a data lakehouse ) have taken over the market, offering more accessible and affordable options for storing data relative to many on-premises solutions.

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Building BI Data Lake Data Governance 52

Monte Carlo

JULY 19, 2023

Its powerful selection of tooling components combine to create a single synchronized and extensible data platform with each layer serving a unique function of the data pipeline. Unlike ogres, however, the cloud data platform isn’t a fairy tale. Data transformation Okay, so your data needs to live in the cloud.

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Building Business Intelligence Cloud Storage BI 96

Monte Carlo

JANUARY 27, 2024

Its powerful selection of tooling components combine to create a single synchronized and extensible data platform with each layer serving a unique function of the data pipeline. Unlike ogres, however, the cloud data platform isn’t a fairy tale. Data transformation Okay, so your data needs to live in the cloud.

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Building Business Intelligence Cloud Storage BI 52

Towards Data Science

JULY 21, 2023

Its powerful selection of tooling components combine to create a single synchronized and extensible data platform with each layer serving a unique function of the data pipeline. Unlike ogres, however, the cloud data platform isn’t a fairy tale. Data transformation Okay, so your data needs to live in the cloud.

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Building Business Intelligence BI Cloud Storage 83