Snowflake

NOVEMBER 2, 2023

Rather than defining schema upfront, a user can decide which data and schema they need for their use case. Snowflake has long supported semi-structured data types and file formats like JSON, XML, Parquet, and more recently storage and processing of unstructured data such as PDF documents, images, videos, and audio files.

Data Lake 97

Data Lake Data Warehouse Cloud Unstructured Data 97

Cloudera

JUNE 3, 2022

Due to the lack of tooling specifically designed for data discovery, exploration, and preliminary analysis, this presents a significant challenge for these teams. . When it comes to the early stages in the data science process, data scientists often find themselves jumping between a wide range of tooling.

Data Analysis 97

Data Analysis PostgreSQL Data Science Machine Learning 97

Cloudera

NOVEMBER 15, 2024

The manual process of switching between tools slows down their work, often leaving them reliant on rudimentary methods of keeping track of their findings. Unstructured data not ready for analysis: Even when defenders finally collect log data, it’s rarely in a format that’s ready for analysis.

Metadata 90

Metadata Unstructured Data Data Lake Government 90

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. Why use PySpark? To set the master URL, use setMaster(value).

Big Data 52

Big Data Data Process Process Kafka 52

ThoughtSpot

MARCH 5, 2024

When creating a dynamic table in Snowflake, you specify the SQL query that will transform the source data. The refresh process automatically computes changes in the source data and merges those updates into the dynamic table. To power these refreshes, compute resources are associated with each dynamic table.

BI 111

BI Datasets Raw Data SQL 111

Snowflake

NOVEMBER 11, 2024

Here’s how Snowflake Cortex AI and Snowflake ML are accelerating the delivery of trusted AI solutions for the most critical generative AI applications: Natural language processing (NLP) for data pipelines: Large language models (LLMs) have a transformative potential, but they often batch inference integration into pipelines, which can be cumbersome.

Unstructured Data 82

Unstructured Data SQL AWS Healthcare 82

Data Engineering Podcast

FEBRUARY 3, 2019

Open Context is a platform for cleaning, curating, and sharing this data. So I decided to focus my energies in research data management. Open Context is an open access data publishing service for archaeology. What are your protocols for determining which data sets you will work with?

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units. scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

FEBRUARY 29, 2024

Get to know more about data science for business. Learning Data Analysis in Excel Data analysis is a process of inspecting, cleaning, transforming and modelling data with an objective of uncover the useful knowledge, results and supporting decision. The best Website to learn Python: w3schools.com.

Data Science 98

Data Science Datasets Machine Learning Database Design 98

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Schema drift on a wide table structure needs an ALTER TABLE statement, whereas the tall table structure does not.

Engineering 88

Engineering Raw Data Data Science Machine Learning 88

Cloudera

DECEMBER 11, 2020

As mentioned in my previous blog on the topic , the recent shift to remote working has seen an increase in conversations around how data is managed. Toolsets and strategies have had to shift to ensure controlled access to data. It established a data governance framework within its enterprise data lake.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Snowflake

JULY 10, 2023

Announced at Summit, we’ve recently added to Snowpark the ability to process files programmatically, with Python in public preview and Java generally available. Data engineers and data scientists can take advantage of Snowflake’s fast engine with secure access to open source libraries for processing images, video, audio, and more.

Unstructured Data 40

Unstructured Data Python Process Scala 40

AltexSoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. GraphX is Spark’s component for processing graph data.

Big Data 52

Big Data Data Process Process Hadoop 52

Cloudera

SEPTEMBER 17, 2020

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization.

Data Warehouse 87

Data Warehouse Unstructured Data Pharmaceutical MySQL 87

Snowflake

DECEMBER 4, 2024

The next evolution in data is making it AI ready. For years, an essential tenet of digital transformation has been to make data accessible, to break down silos so that the enterprise can draw value from all of its data. For this reason, internal-facing AI will continue to be the focus for the next couple of years.

Unstructured Data 68

Unstructured Data Data Lake Deep Learning Structured Data 68

Edureka

JULY 5, 2024

Proper data pre-processing and data cleaning in data analysis constitute the starting point and foundation for effective decision-making, though it can be the most tiresome phase. simultaneously making raw data efficient to form insights. What is Tableau Prep ?

Data Preparation 40

Data Preparation Process BI ETL Tools 40

Cloudera

SEPTEMBER 29, 2021

Among governments’ priorities are encouraging digital adoption, facilitating access and usage of relevant government services alongside enabling more digital transactions. Through processing vast amounts of structured and semi-structured data, AI and machine learning enabled effective fraud prevention in real-time on a national scale. .

Medical 88

Medical Government Hospitality Electronics 88

U-Next

MARCH 1, 2023

Being a hybrid role, Data Engineer requires technical as well as business skills. They build scalable data processing pipelines and provide analytical insights to business users. A Data Engineer also designs, builds, integrates, and manages large-scale data processing systems. What is AWS Kinesis?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Knowledge Hut

DECEMBER 26, 2023

According to the Cybercrime Magazine, the global data storage is projected to be 200+ zettabytes (1 zettabyte = 10 12 gigabytes) by 2025, including the data stored on the cloud, personal devices, and public and private IT infrastructures. You can execute this by learning data science with python and working on real projects.

Data Science 97

Data Science BI Business Intelligence Machine Learning 97

Snowflake

SEPTEMBER 19, 2023

Why AI has everyone’s attention, what it means for different data roles, and how Alteryx and Snowflake are bringing AI to data use cases There’s a llama on the loose! With all the hoopla around AI, there’s a lot to get up to speed on—especially the implications this technology has for data analytics.

Machine Learning 101

Machine Learning Unstructured Data Data Analytics Government 101

AltexSoft

OCTOBER 25, 2021

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. What is Natural Language Processing? Unstructured data is unavoidable, yet extremely valuable. Streamline administrative processes.

Medical 52

Medical Healthcare Process Hospitality 52

Edureka

JUNE 7, 2024

Unlike traditional AI systems that operate on pre-existing data, generative AI models learn the underlying patterns and relationships within their training data and use that knowledge to create novel outputs that did not previously exist. This allows for a more controlled and step-by-step text generation process.

Deep Learning 114

Deep Learning Media Manufacturing Algorithm 114

Cloudera

OCTOBER 28, 2021

Commercial Lines insurers generally do not analyze the full range of their data, nor do they always have the right processes and technology in place to enable the collection, storage, and analysis to operationalize the data. There is a wealth of data now available to make this possible.

Insurance 102

Insurance Transportation Unstructured Data Manufacturing 102

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 92

Systems Hadoop Metadata Telecommunication 92

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 118

IT Unstructured Data Data Architecture Government 118

Cloudera

JULY 26, 2021

The alleviation of infrastructure and computational constraints associated with solely on-premises data platforms; Data Products can now use different deployment models (e.g., The proliferation of real-time processing by deploying event-driven architectures (e.g., Deep Java Learning, Apache Spark 3.x,

Generalist 120

Generalist Telecommunication Healthcare Data Science 120

Monte Carlo

JUNE 6, 2023

Some teams view data quality mainly as a technical challenge while others look at it as a business or process problem. I have spoken to dozens of data leaders in the past year to understand how they approach data quality as part of their overall organizational goals.

Data Governance 98

Data Governance Government Data Data Engineering 98

Confluent

OCTOBER 3, 2019

We recently launched a new artificial intelligence (AI) data extraction API called Scrapinghub AutoExtract , which turns article and product pages into structured data. At Scrapinghub, we specialize in web data extraction , and our products empower everyone from programmers to CEOs to extract web data quickly and effectively.

Kafka 16

Kafka Cloud Amazon Web Services Google Cloud 16

Data Engineering Weekly

MAY 5, 2024

The motivation for Machine Unlearning is critical from the privacy perspective and for model correction, fixing outdated knowledge, and access revocation of the training dataset. The author expands on the possibility of unified data platforms. A key thought-provoking moment for me while reading the article is this quote.

Data Engineering 69

Data Engineering Data Engineer Engineering Google Cloud 69

Engineering at Meta

MARCH 18, 2024

Logarithm’s data model Logarithm represents logs as a named log stream of (host-local) time-ordered sequences of immutable unstructured text, corresponding to a single log file. A process can emit multiple log streams ( stdout , stderr , and custom log files). in PyTorch). Lightweight disaggregated secondary indices.

Engineering 105

Engineering Metadata Architecture Designing 105

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. Open data lakehouse.

Unstructured Data 80

Unstructured Data Data Lake Data Architecture Data 80

Monte Carlo

FEBRUARY 12, 2024

To differentiate and expand the usefulness of these models, organizations must augment them with first-party data – typically via a process called RAG (retrieval augmented generation). Today, this first-party data mostly lives in two types of data repositories. Quality : Is the data itself anomalous?

Database 72

Database Unstructured Data Data Pipeline Metadata 72

Netflix Tech

OCTOBER 27, 2020

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The processed data is typically stored as data warehouse tables in AWS S3.

Data Warehouse 101

Data Warehouse Datasets Data Big Data 101

Cloudera

OCTOBER 17, 2023

Five Takeaways from Current 2023: 1- The people have spoken and Apache Flink is the de facto standard for stream processing This may seem obvious to many who are already familiar with Flink, but it is worth pointing out. Flink is here to stay. It makes perfect sense that Apache Flink has emerged as the standard.

Kafka 84

Kafka Database-centric Pipeline-centric Database 84

Confluent

JUNE 13, 2019

To fully characterize transient objects, astronomers need to gather data from other telescopes at different wavelengths at nearly the same time. Astronomers need to be able to collect, process, characterize, and distribute data on these objects in near real time, especially for time-sensitive events. Armed with a Ph.D.

Kafka 102

Kafka Bytes Data Pipeline Python 102

Netflix Tech

DECEMBER 14, 2018

under varying load conditions as well as a wide variety of access patterns; (b) scalability?—?persisting data access semantics that guarantee repeatable data read behavior for client applications. data access semantics that guarantee repeatable data read behavior for client applications.

Media 97

Media Database Metadata Data Schemas 97

Knowledge Hut

JANUARY 29, 2024

In today's data-driven world, where information reigns supreme, businesses rely on data to guide their decisions and strategies. However, the sheer volume and complexity of raw data from various sources can often resemble a chaotic jigsaw puzzle.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52