Cloudera

MARCH 6, 2018

People are gravitating to the analytics services of the large public cloud providers because the “house-brand” offerings seem to be the easiest choice. This leads to extra cost, effort, and risk to stitch together a sub-optimal platform for multi-disciplinary, cloud-based analytics applications.

Cloud 40

Cloud Metadata Big Data AWS 40

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. A lightinign fast analytics app built with our system. The cloud is better.

Engineering 68

Engineering Data Lake AWS BI 68

Christophe Blefari

JANUARY 7, 2023

Introducing ADBC: Database Access for Apache Arrow — When I see "minimal-overhead alternative to JDBC/ODBC for analytical applications" I'm instantly in. Qlik and Talend are two old BI giants. They had obviously been challenged by the cloud vendors and the modern data stack vision that does not include them.

Data Science 130

Data Science Data BI Kafka 130

Knowledge Hut

MARCH 15, 2024

It holds the second-largest proportion of the cloud market. You can work as a developer, cloud architect, admin, or solutions specialist for Azure. Since every business is gradually moving to the cloud, you may work in any field. It may be used to prepare for Microsoft Azure or cloud services tests.

Cloud Computing 52

Cloud Computing Algorithm Certification SQL 52

Rockset

JUNE 21, 2022

We’re excited to announce that Rockset’s new connector with Snowflake is now available and can increase cost efficiencies for customers building real-time analytics applications. What’s Needed for Real-Time Analytics? These real-time, user-facing applications include personalization , gamification or in-app analytics.

Kafka 52

Kafka Data Warehouse BI Analytics Application 52

U-Next

AUGUST 23, 2022

A rapidly expanding data visualization tool called Tableau Software is creating a stir within Business Intelligence (BI) sector. There are several applications for Tableau software. On-premises or in the cloud, you can securely and flexibly manage access to data, connect privileges, and analytics. Tableau Basics.

BI 52

BI Amazon Web Services Business Intelligence Database 52

Rockset

FEBRUARY 2, 2022

Let’s explore five ways to run MongoDB analytics, along with the pros and cons of each method. 1 – Query MongoDB Directly The first and most direct approach is to run your analytical queries directly against MongoDB. There are quite a few of these on the market, with each trying to enable business intelligence (BI) on MongoDB.

MongoDB 52

MongoDB NoSQL Data Warehouse BI 52

Rockset

DECEMBER 9, 2021

Lifting-and-shifting their big data environment into the cloud only made things more complex. The modern data stack introduced a set of cloud-native data solutions such as Fivetran for data ingestion, Snowflake, Redshift or BigQuery for data warehousing , and Looker or Mode for data visualization. The problem?

Transportation 52

Transportation BI SQL Data Warehouse 52

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. Source Code: Anomaly Detection in Cloud Servers 2.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Rockset

MAY 17, 2022

Complex SQL queries have long been commonplace in business intelligence (BI). The truth is that modern cloud native SQL databases support all of the key features necessary for real-time analytics , including: Mutable data for incredibly fast data ingestion and smooth handling of late-arriving events. Learn more at rockset.com.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Change data capture (CDC) streams from OLTP databases, which may provide sales, demographic or inventory data, are another valuable source of data for real-time analytics use cases.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Cloudera

NOVEMBER 2, 2020

It has the key elements of fast ingest, fast storage, and immediate querying for BI purposes. These include stream processing/analytics, batch processing, tiered storage (i.e. Cloudera offers a platform, Cloudera Data Platform (CDP), for building end-to-end data applications in both the public and private cloud.

Data Warehouse 94

Data Warehouse Kafka Lambda Architecture Telecommunication 94

Cloudera

DECEMBER 7, 2017

Cloud promises many advantages as an environment for machine learning and analytics. Cloud makes it fast and easy to spin up resources for new applications. Cloud offers elasticity of those resources to efficiently support transient analytics workloads and data pipelines.

Building 40

Building Management Government BI 40

Cloudera

JUNE 16, 2022

Building real-time data analytics pipelines is a complex problem, and we saw customers struggle using processing frameworks such as Apache Storm, Spark Streaming, and Kafka Streams. . Better yet, it works in any cloud environment. Not in the manufacturing space? Getting started today.

Kafka 86

Kafka Manufacturing Data Lake SQL 86

AltexSoft

OCTOBER 21, 2022

A single cluster can span across multiple data centers and cloud facilities. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. Depending on the type of deployment (cloud or on-premise), cluster size, and the number of integrations, the deployment may take days to weeks to even months.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Rockset

FEBRUARY 9, 2021

Amazon Simple Storage Service (Amazon S3) is one of the leading cloud object storage services available. It uses an HTTP interface, making it easy for application developers to integrate S3 into their applications. Athena is a serverless query service provided by Amazon to query the data stored in Amazon S3 using standard SQL.

Data Lake 40

Data Lake Business Intelligence SQL Datasets 40

phData: Data Engineering

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

MAY 20, 2015

The company targets to deliver values to its customers through the free SaaS based analytics applications so that it can build credibility with the clients to encourage them to buy more. The products and services of Cloudera are changing the economics of big data analysis , BI, data processing and warehousing through Hadooponomics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications.

Big Data 52

Big Data Coding Project Hadoop 52