AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Velocity Big Data is often characterized by high data velocity, requiring real-time or near real-time data ingestion and processing. It involves handling streams of data that are generated rapidly, such as sensor data or social media feeds.

Big Data 52

Big Data Datasets Data Analysis Media 52

Knowledge Hut

APRIL 23, 2024

Traditional tools and methods cannot effectively manage and analyze information gleaned from big data within a reasonable timeframe. These data sets consist of extensive and intricate data from diverse sources, including business transactions, social media interactions, and sensor data.

Big Data 52

Big Data Media Datasets Unstructured Data 52

AltexSoft

MAY 12, 2023

Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. Unlike structured data, which is organized into neat rows and columns within a database, unstructured data is an unsorted and vast information collection.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Data Engineering Weekly

NOVEMBER 20, 2022

Google AI: The Data Cards Playbook: A Toolkit for Transparency in Dataset Documentation Google published Data Cards , a dataset documentation framework aimed at increasing transparency across dataset lifecycles. With Upsolver SQLake, you build a pipeline for data in motion simply by writing a SQL query defining your transformation.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Knowledge Hut

JANUARY 18, 2024

Let us now look into the differences between AI and Data Science: Data Science vs Artificial Intelligence [Comparison Table] SI Parameters Data Science Artificial Intelligence 1 Basics Involves processes such as data ingestion, analysis, visualization, and communication of insights derived.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Snowflake

APRIL 20, 2023

Data Pipelines Snowpipe Streaming – public preview While data generated in real time is valuable, it is more valuable when paired with historical data that helps provide context. The company’s data is highly accurate, which makes deriving insights easy and decision-making truly fact based.

Medical 57

Medical Retail Python Pharmaceutical 57