Rockset

AUGUST 25, 2021

It’s simply too expensive to store all the raw data and simply too slow to run batch processes to pre-aggregate it. One common example is a mobile app, where every activity is recorded as an event, resulting in millions of events per day streaming in. Efficiency.

Aggregated Data 52

Aggregated Data Hadoop SQL Data Lake 52

Striim

AUGUST 22, 2024

Streaming analytics focuses on analyzing data in motion, unlike traditional analytics, which deals with data stored in databases or data warehouses. Because of this, streaming analytics is especially impactful for fraud detection, log analysis, and sensor data processing use cases.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

AltexSoft

OCTOBER 21, 2022

This scenario involves three main characters — publishers, subscribers, and a message or event broker. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker. Kafka cluster and brokers.

Kafka 93

Kafka Hadoop Big Data ETL Tools 93

Knowledge Hut

JANUARY 19, 2024

New Analytics Strategy vs. Existing Analytics Strategy Business Intelligence is concerned with aggregated data collected from various sources (like databases) and analyzed for insights about a business' performance. In contrast, Business Analytics involves an analytical approach to solving problems within a business context.

Business Intelligence 52

Business Intelligence BI Business Analyst Aggregated Data 52

Rockset

MARCH 1, 2023

In addition, Rockset provides fast data access through the use of more performant hot storage, while cloud storage is used for durability. Rockset’s ability to exploit the cloud makes complete isolation of compute resources possible.

Architecture 59

Architecture AWS SQL Cloud Storage 59

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. In the event that they are not the same, what are the difference s? Data lakes, however, are sometimes used as cheap storage with the expectation that they are used for analytics.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Confluent

FEBRUARY 6, 2019

Say you wanted to build one integration pipeline from MQTT to Kafka with KSQL for data preprocessing, and use Kafka Connect for data ingestion into HDFS, AWS S3 or Google Cloud Storage, where you do the model training. New MQTT input data can directly be used in real time to make predictions.

Machine Learning 107

Machine Learning Python Kafka Java 107