Ascend.io

FEBRUARY 23, 2024

Before we explore the specific requirements your AI data platform, let’s evaluate your technical foundation’s readiness for AI. Critical considerations include: Do you have the cloud capabilities necessary to scale with AI’s demands? Is your data environment diverse and accessible enough to fuel AI algorithms?

Cloud Storage 52

Cloud Storage Data Ingestion Machine Learning Algorithm 52

Monte Carlo

APRIL 24, 2023

By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases. See our post: Data Lakes vs. Data Warehouses.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

ThoughtSpot

MAY 31, 2023

Architecture Let's start with the big picture and tackle how we adjusted our cloud architecture with additional internal and external interfaces to integrate LLM. Search and model assist hints are stored in the tenant specific cloud storage bucket.

Data Security 86

Data Security Metadata Transportation Data Warehouse 86

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Source : A stream of sensor data represented as a directed acyclic graph.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

phData: Data Engineering

APRIL 4, 2023

Customers who don’t necessarily want to put their data directly into a data warehouse like the Snowflake Data Cloud can now use Fivetran to build a performant, governed, managed dataset on top of S3 which can still be efficiently queried and manipulated from within their query engine of choice.

Data Lake 52

Data Lake Amazon Web Services Data Cleanse Data Warehouse 52

Ascend.io

JUNE 22, 2023

Ascend is thrilled to announce the availability of our newest feature: the ability to deliver data directly to the MotherDuck analytics platform! Get started with a free developer-tier Ascend Cloud environment and begin loading your data into MotherDuck today ( docs )!

NoSQL 52

NoSQL MySQL Google Cloud Data Pipeline 52

Towards Data Science

MARCH 6, 2023

On-premise and cloud working together to deliver a data product Photo by Toro Tseleng on Unsplash Developing a data pipeline is somewhat similar to playing with lego, you mentalize what needs to be achieved (the data requirements), choose the pieces (software, tools, platforms), and fit them together.

Google Cloud 86

Google Cloud Cloud Storage Data Pipeline Cloud 86

Cloudera

SEPTEMBER 15, 2022

A key area of focus for the symposium this year was the design and deployment of modern data platforms. Luke: Let’s talk about some of the fundamentals of modern data architecture. What is a data fabric? Mark: Gartner states that a data fabric “enables frictionless access and sharing of data in a distributed data environment.”

Data Lake 78

Data Lake Analytics Application Cloud Storage Architecture 78

RandomTrees

SEPTEMBER 6, 2020

Snowflake Overview A data warehouse is a critical part of any business organization. Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS).

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

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.

Data Engineering 52

Data Engineering Data Engineer Engineering Business Intelligence 52

Knowledge Hut

NOVEMBER 16, 2023

Cloud computing, along with data science has been the buzzword for quite some time now. Companies have moved towards cloud architecture for their data storage and computing needs. There are some renowned cloud players like Amazon Web Services, Google Cloud, IBM Watson, etc.,

Data Science 52

Data Science Technology Programming Language Cloud Computing 52

Hevo

MAY 8, 2023

The exponential rate of data generation in every modern business from various SaaS applications, Marketing Channels, etc. has compelled them to move from On-premise databases to Cloud-Based Data Warehouses.

Data Warehouse 52

Data Warehouse Machine Learning Cloud Database 52

Cloudera

FEBRUARY 7, 2019

The company sought a data management platform that would allow its enterprise to handle greater data variety, velocity and volume in a cost-effective manner. Enabling this transformation is the HDP platform, along with SAS Viya on Google Cloud , which has delivered machine learning models and personalization at scale.

Utilities 63

Utilities Big Data Google Cloud Data Analytics 63

Knowledge Hut

APRIL 25, 2023

Data engineers add meaning to the data for companies, be it by designing infrastructure or developing algorithms. The practice requires them to use a mix of various programming languages, data warehouses, and tools. While they go about it - enter big data data engineer tools. What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

ProjectPro

FEBRUARY 8, 2023

ETL stands for Extract, Transform, and Load, which involves extracting data from various sources, transforming the data into a format suitable for analysis, and loading the data into a destination system such as a data warehouse. Works on data storage and retrieval, data processing, and data visualization.

ETL Tools 52

ETL Tools Data Cleanse Data Warehouse Big Data 52

Data Engineering Podcast

SEPTEMBER 22, 2019

Summary Object storage is quickly becoming the unifying layer for data intensive applications and analytics. Modern, cloud oriented data warehouses and data lakes both rely on the durability and ease of use that it provides. How do you approach project governance and sustainability?

AWS 100

AWS Google Cloud Cloud Storage Data Lake 100

Striim

FEBRUARY 10, 2023

It provides networking solutions to support the world’s largest telecommunications service providers, submarine network operators, data and cloud operators, and large enterprises. Quickly turn data into actionable insights that help Macy’s deliver quality digital customer experiences and improve operational efficiencies.

Data Analytics 52

Data Analytics Telecommunication Insurance Google Cloud 52

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.

Machine Learning 94

Machine Learning Data Science Data Security Data Storage 94

Rockset

MARCH 5, 2021

Understanding the space-time tradeoff in data analytics In computer science, a space-time tradeoff is a way of solving a problem or calculation in less time by using more storage space, or by solving a problem in very little space by spending a long time. However for each query it needs to scan your data.

Cloud Storage 52

Cloud Storage Data Ingestion Data Warehouse Computer Science 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.

Data Ingestion 40

Data Ingestion Cloud Storage Data Warehouse Data Lake 40

Knowledge Hut

JANUARY 19, 2024

Because it involves analyzing large amounts of data from multiple sources, business analytics can be a time- and resource-intensive process. Tools Business intelligence uses various tools to collect, analyze, and report data. Business analytics uses predictive models to forecast future trends.

Business Intelligence 52

Business Intelligence BI Business Analyst Aggregated Data 52

Cloudera

JULY 15, 2019

After taking this course, you’ll understand how databases provide structure to data and how this has changed as the volume and variety of data have increased. You’ll compare operational and analytic databases and learn what differentiates a modern distributed data warehouse.

Education 55

Education Data Analysis Big Data SQL 55

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.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

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.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

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).

Cloud Storage 79

Cloud Storage Accessible Accessibility Cloud 79

Rockset

JANUARY 25, 2022

Snowflake’s data cloud enables companies to store and share data, then analyze this data for business intelligence. Although Snowflake is a great tool, sometimes querying vast amounts of data runs slower than your applications — and users — require.

Business Intelligence 52

Business Intelligence Cloud Storage Data Warehouse Cloud 52

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.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

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). Multiple open source projects and vendors have been working together to make this vision a reality.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

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?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

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?

Database 40

Database Google Cloud AWS Cloud Storage 40

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?

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

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.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

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.

Google Cloud 52

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.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Rockset

SEPTEMBER 15, 2020

Before the advent of real-time databases, a user would typically use a data pipeline to clean and homogenize all the fields, flatten nested fields, denormalize nested objects and then write it out it to a data warehouse like Redshift or Snowflake. The data warehouse is then used to gather insights from their data.

Bytes 40

Bytes Database Data Warehouse Data Pipeline 40

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. There are times when the data is structured , but it is often messy since it is ingested directly from the data source. What is Data Warehouse? . Data Warehouse in DBMS: .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

dbt Developer Hub

NOVEMBER 22, 2022

Once your data warehouse is built out, the vast majority of your data will have come from other SaaS tools, internal databases, or customer data platforms (CDPs). Spreadsheets are the Swiss army knife of data processing. But there’s another unsung hero of the analytics engineering toolkit: the humble spreadsheet.

Data Warehouse 52

Data Warehouse ETL Tools Google Cloud Cloud Storage 52