Edureka

JUNE 7, 2024

paintings, songs, code) Historical data relevant to the prediction task (e.g., 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.

Deep Learning 114

Deep Learning Media Manufacturing Algorithm 114

Knowledge Hut

APRIL 23, 2024

Big data has revolutionized the world of data science altogether. With the help of big data analytics, we can gain insights from large datasets and reveal previously concealed patterns, trends, and correlations. Learn more about the 4 Vs of big data with examples by going for the Big Data certification online course.

Big Data 52

Big Data Media Datasets Unstructured Data 52

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The motivation for Machine Unlearning is critical from the privacy perspective and for model correction, fixing outdated knowledge, and access revocation of the training dataset.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 67

Data Engineering Data Engineer Engineering Google Cloud 67

Knowledge Hut

APRIL 23, 2024

Data storing and processing is nothing new; organizations have been doing it for a few decades to reap valuable insights. Compared to that, Big Data is a much more recently derived term. So, what exactly is the difference between Traditional Data and Big Data? Smaller and more cost-effective ways of managing data.

Big Data 52

Big Data Relational Database Data Datasets 52

Knowledge Hut

JANUARY 30, 2024

Whether you're a seasoned data scientist or just stepping into the world of data, come with me as we unravel the secrets of data extraction and learn how it empowers us to unleash the full potential of data. What is data extraction? What is the purpose of extracting data?

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Monte Carlo

MAY 28, 2024

This involves connecting to multiple data sources, using extract, transform, load ( ETL ) processes to standardize the data, and using orchestration tools to manage the flow of data so that it’s continuously and reliably imported – and readily available for analysis and decision-making.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Striim

MAY 1, 2024

UPS Capital recognizes the challenges faced by its customers in securing their package delivery ecosystem and is harnessing digital capabilities and data access to redefine traditional approaches, ensuring improved customer experiences and combating shipping loss.

Google Cloud 52

Google Cloud Insurance Finance Machine Learning 52

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. The dataset can be either structured or unstructured or both.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Knowledge Hut

JUNE 28, 2023

The answer lies in the strategic utilization of business intelligence for data mining (BI). Although these terms are sometimes used interchangeably, they carry distinct meanings and play different roles in this process. Process of analyzing, collecting, and presenting data to support decision-making.

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

Knowledge Hut

MARCH 27, 2024

An ordered set of data kept in a computer system and typically managed by a database management system (DBMS) is called a database. Table modeling of the data in standard databases facilitates efficient searching and processing. SQL, or structured query language, is widely used for writing and querying data.

Database 52

Database Relational Database Algorithm PostgreSQL 52

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

Edureka

FEBRUARY 8, 2024

Different instance types offer varying levels of compute power, memory, and storage, which directly influence tasks such as data processing, application responsiveness, and overall system throughput. Key Factors to Consider- When choosing an AWS instance type, several key factors should guide your decision-making process.

AWS 52

AWS NoSQL Deep Learning Datasets 52

Ascend.io

FEBRUARY 28, 2024

Engineers ensure the availability of clean, structured data, a necessity for AI systems to learn from patterns, make accurate predictions, and automate decision-making processes. By ensuring data is well-organized and readily accessible, data engineers empower AI systems to deliver targeted and effective solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Knowledge Hut

DECEMBER 21, 2023

This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed. To establish a career in big data, you need to be knowledgeable about some concepts, Hadoop being one of them. What is Hadoop?

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Monte Carlo

FEBRUARY 27, 2024

Right now, RAG is the essential technique to make GenAI models useful by giving an LLM access to an integrated, dynamic dataset while responding to prompts. But instead of integrating a dynamic database to an existing LLM, fine-tuning involves training an LLM on a smaller, task-specific, and labeled dataset.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

Knowledge Hut

JANUARY 19, 2024

Entering the world of data science is a strategic move in the 21st century, known for its lucrative opportunities. With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. Recognizing the growing need for data scientists, institutions worldwide are intensifying efforts to meet this demand.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Towards Data Science

MAY 14, 2024

Typically, as shown in the image above, Dataform takes raw data, transform it with all the engineering best practices and output a properly structured data ready for consumption. In Part 2, I would provide a walkthrough of the Terraform setup showing how to implement the least access control when provisioning Dataform.

Data Pipeline 68

Data Pipeline Coding Raw Data Accessible 68

Knowledge Hut

MARCH 22, 2024

On the other hand, in non-linear data structures, the elements do not form a sequence. The choice between using a linear or non-linear data structure depends on the access patterns needed for the application. More flexible in terms of data organisation and access. Less complex memory management.

Algorithm 52

Algorithm Data Datasets Accessible 52

Knowledge Hut

MARCH 20, 2024

Data type defines the kind of value that can be stored in a variable or expression, acting as a classification system for data. Data structure, on the other hand, is a way to arrange and store data in computer memory so that it may be accessed and altered quickly. What is Data Structure?

Computer Science 52

Computer Science Programming Language Algorithm Software Engineer 52

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

Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

SQL 69

SQL Data Analytics Hadoop Raw Data 69

Data Engineering Podcast

FEBRUARY 3, 2019

Open Context is a platform for cleaning, curating, and sharing this data. Open Context is an open access data publishing service for archaeology. It started because we need better ways of dissminating structured data and digital media than is possible with conventional articles, books and reports.

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

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 92

Data Analysis PostgreSQL Data Science SQL 92

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

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Towards Data Science

MARCH 5, 2024

The storage system is using Capacitor, a proprietary columnar storage format by Google for semi-structured data and the file system underneath is Colossus, the distributed file system by Google. In that case, queries are still processed using the BigQuery compute infrastructure but read data from GCS instead.

Bytes 67

Bytes Google Cloud Cloud Storage Utilities 67

Monte Carlo

JULY 13, 2023

To effectively manage and analyze this data, data engineering teams must navigate a wide range of challenges, including data access, security, compliance, and data observability. Automation is a missing link in many organizations’ efforts toward data operationalization. Automating self-service access.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Knowledge Hut

SEPTEMBER 26, 2023

The insights derived from the data in hand are then turned into impressive business intelligence visuals such as graphs or charts for the executive management to make strategic decisions. In this post, we will discuss the top power BI developer skills required to access Microsoft’s power business intelligence software.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

AltexSoft

AUGUST 29, 2023

Another distinction is the ETL vs. ELT choice: In data warehouses, Extract and Transform processes usually occur before data is loaded into the warehouse. Many organizations also deploy data marts , which are dedicated storage repositories for specific business lines or workgroups. Structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Rockset

MAY 21, 2024

Secondly, as LLMs are trained on datasets that are static and often outdated by the time they're deployed, they are unable to provide accurate or relevant information about recent developments or trends. When a prompt is given to the LLM, RAG first uses the prompt to pull relevant information from an external data source.

Building 52

Building Utilities Datasets Database 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

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. link] The short YouTube video gives a nice overview of the Data Cards.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Knowledge Hut

JULY 26, 2023

Veracity meaning in big data is the degree of accuracy and trustworthiness of data, which plays a pivotal role in deriving meaningful insights and making informed decisions. This blog will delve into the importance of veracity in Big Data, exploring why accuracy matters and how it impacts decision-making processes.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Confluent

AUGUST 29, 2019

Stream processing engines like KSQL furthermore give you the ability to manipulate all of this fluently. In an identity/access management application, it’s the relationships between roles and their privileges that matters most. Nodes are like our data entities (in this example, we use Person ). For example, Cory FRIENDED Levi.

Kafka 55

Kafka Process Algorithm Cloud 55

Towards Data Science

JUNE 8, 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 73

Data Governance Government Generalist Data Engineering 73

Monte Carlo

FEBRUARY 26, 2024

It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems. Governance can be handled at a granular level and access control becomes part of the custom workflow.

Metadata 52

Metadata Government Data Data Governance 52