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

AltexSoft

SEPTEMBER 23, 2021

The main purpose of a DW is to enable analytics: It is designed to source raw historical data, apply transformations, and store it in a structured format. This type of storage is a standard part of any business intelligence (BI) system, an analytical interface where users can query data to make business decisions.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Rockset

MAY 17, 2022

Complex SQL queries have long been commonplace in business intelligence (BI). Or a market news provider that needs to monitor and ensure that its financial customers are getting accurate, relevant updates within the narrow windows for profitable trades.

SQL 52

SQL NoSQL Hadoop MongoDB 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. In addition to understanding the attributes of an RTDW, it is useful to look at the types of applications that can be built within the RTDW category.

Data Warehouse 96

Data Warehouse Kafka Lambda Architecture BI 96

Cloudera

DECEMBER 7, 2017

Now we are releasing the reference architecture for you build your own self-managed SDX foundation for all your cloud-based data and analytics applications. Cloud data that is already curated with business context, not needing IT to rebuild schemas or business definitions.

Building 40

Building Management Government BI 40

Rockset

FEBRUARY 9, 2021

Because it integrates easily with S3, is serverless, and uses a familiar language, Athena has become the default service for most business intelligence (BI) decision makers to query the large amounts of (usually streaming) data coming into their object stores. This is definitely not a good user experience.

Data Lake 40

Data Lake Business Intelligence SQL Datasets 40

Knowledge Hut

JUNE 26, 2023

Business intelligence solutions like as Power BI, Tableau, and Looker may assist companies in mitigating operational risk and achieving maximum efficiency in terms of operations enablement by assisting businesses in making choices that are supported by data.

Data Engineer 98

Data Engineer Data Engineering Coding Project 98

Cloudera

MAY 16, 2018

Arcadia Data partners with Cloudera to realize their shared vision of enabling subject matter experts to gain business insight from modern data platforms.

Data Lake 42

Data Lake Electronics Media Unstructured Data 42

AltexSoft

OCTOBER 21, 2022

A subscriber is a receiving program such as an end-user app or business intelligence tool. Hadoop fits heavy, not time-critical analytics applications that generate insights for long-term planning and strategic decisions. Kafka is more about building services that power daily business operations. Kafka vs ETL.

Kafka 93

Kafka Hadoop Big Data ETL Tools 93

ProjectPro

MAY 20, 2015

Fred Shilmover, CEO of InsightSquared says- "It's an exciting time to be in the big data analytics space pointing to recent developments such as Tableau Software's highly successful IPO and a $125 million funding round for Domo. We do not service the pizza shop at the end of street.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

AltexSoft

JULY 18, 2023

It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs. Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications.

Big Data 52

Big Data Data Process Process Hadoop 52

U-Next

AUGUST 11, 2022

BI tools are different types of application software that collect and process huge amounts of unstructured data from internal and external sources. The enormous amounts of data being created provide a problem for firms of all kinds, making it tougher year after year to ensure that all business operations are under check.

Business Intelligence 40

Business Intelligence BI Unstructured Data Programming 40

phData: Data Engineering

JULY 18, 2023

CDWs are designed for running large and complex queries across vast amounts of data, making them ideal for centralizing an organization’s analytical data for the purpose of business intelligence and data analytics applications. It should also enable easy sharing of insights across the organization.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Cloudera

JUNE 16, 2022

This blog aims to answer two questions as illustrated in the diagram below: How have stream processing requirements and use cases evolved as more organizations shift to “streaming first” architectures and attempt to build streaming analytics pipelines?

Kafka 87

Kafka Manufacturing Data Lake SQL 87