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

Data Engineering Weekly

APRIL 7, 2024

We index only top-tier tables, promoting the use of these higher-quality datasets. I strongly believe the concept of Data Product will play a bigger role in data engineering. The highlight for me is, There is an ongoing table standardization effort at Pinterest to add tiering for the tables.

Data Engineering 70

Data Engineering Data Engineer Engineering Unstructured Data 70

Knowledge Hut

JANUARY 30, 2024

In summary, data extraction is a fundamental step in data-driven decision-making and analytics, enabling the exploration and utilization of valuable insights within an organization's data ecosystem. What is the purpose of extracting data? The process of discovering patterns, trends, and insights within large datasets.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

MARCH 27, 2024

These are the situations where having a lot of data stored in one location and being able to access it quickly are necessary. What is a Data Structure? Using a data structure allows you to efficiently arrange data on a computer. Flexibility: Offers scalability to manage extensive datasets efficiently.

Database 52

Database Algorithm Relational Database PostgreSQL 52

Knowledge Hut

JUNE 28, 2023

Parameter Data Mining Business Intelligence (BI) Definition The process of uncovering patterns, relationships, and insights from extensive datasets. Process of analyzing, collecting, and presenting data to support decision-making. Focus Exploration and discovery of hidden patterns and trends in data.

Data Mining 52

Data Mining Business Intelligence BI Datasets 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

JANUARY 29, 2024

Data wrangling offers several benefits, such as: Usable Data: Data wrangling converts raw data into a format suitable for analysis, ensuring the quality and integrity of the data used for downstream processes. Tabula : A versatile tool suitable for all data types, making it accessible for a wide range of users.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

Ascend.io

FEBRUARY 28, 2024

Read More: AI Data Platform: Key Requirements for Fueling AI Initiatives How Data Engineering Enables AI Data engineering is the backbone of AI’s potential to transform industries , offering the essential infrastructure that powers AI algorithms.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Edureka

FEBRUARY 8, 2024

Use cases for memory-optimized instances include- Database Servers- Applications like relational databases benefit from the higher memory capacity to store and retrieve data efficiently. In-Memory Caching- Memory-optimized instances are suitable for in-memory caching solutions, enhancing the speed of data access.

AWS 52

AWS NoSQL Deep Learning Datasets 52

Knowledge Hut

JANUARY 19, 2024

Embracing data science isn't just about understanding numbers; it's about wielding the power to make impactful decisions. Imagine having the ability to extract meaningful insights from diverse datasets, being the architect of informed strategies that drive business success. That's the promise of a career in data science.

Data Science 52

Data Science Machine Learning Datasets Algorithm 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

DECEMBER 21, 2023

Hadoop helps in data mining, predictive analytics, and ML applications. Why are Hadoop Big Data Tools Needed? With the help of Hadoop big data tools, organizations can make decisions that will be based on the analysis of multiple datasets and variables, and not just small samples or anecdotal incidents.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Data Engineering Podcast

FEBRUARY 3, 2019

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. What are your protocols for determining which data sets you will work with?

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

Monte Carlo

JUNE 6, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Having the data engineering team lead the response to data quality is by far the most common pattern. It is deployed by about half of all organizations that use a modern data stack.

Data Governance 98

Data Governance Government Data Data Engineering 98

Cloudera

JUNE 3, 2022

When it comes to the early stages in the data science process, data scientists often find themselves jumping between a wide range of tooling. First of all, there’s the question of what data is currently available within their organization, where it is, and how it can be accessed.

Data Analysis 88

Data Analysis PostgreSQL Data Science SQL 88

Monte Carlo

JULY 13, 2023

Data-driven organizations generate, collect, and store vast amounts of data. 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. Automating self-service access.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Towards Data Science

JUNE 8, 2023

Now, let’s take a closer look at the strengths and weaknesses of the most popular data quality team structures. Data engineering Photo by Luke Chesser on Unsplash Having the data engineering team lead the response to data quality is by far the most common pattern. Quality falls under their remit as well.

Data Governance 78

Data Governance Government Generalist Data Engineering 78

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Raw data store section.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

MARCH 27, 2024

So long as they have access to a few brief notes, it becomes easy for students to review and go over the fundamental ideas and techniques. Because of its complete accessibility, user-friendliness, and strong community support, Python is the most popular programming language among aficionados for machine learning.

Machine Learning 52

Machine Learning Deep Learning Algorithm Certification 52

Monte Carlo

APRIL 24, 2023

Amazon S3 and/or Lake Formation Amazon S3 is a popular storage platform to build and store data lakes thanks to its high availability and low latency access. S3 has seamless integration with the AWS ecosystem including AWS Glue for data cataloging, Amazon Athena for ad-hoc querying, and Amazon Redshift for data warehousing.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

ProjectPro

SEPTEMBER 9, 2021

The datasets are usually present in Hadoop Distributed File Systems and other databases integrated with the platform. Hive is built on top of Hadoop and provides the measures to read, write, and manage the data. Apache Spark , on the other hand, is an analytics framework to process high-volume datasets.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

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

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is used for data science, meaning that we utilize the capabilities of this NoSQL database system as part of our data analysis and data modeling processes, which fall under the realm of data science. There are several benefits to MongoDB for data science operations.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Rockset

JULY 29, 2022

This consistency promotes data integrity, so you can trust the insights to make informed decisions. Additionally, data warehouses are great at offering historical intelligence. However, organizations today are moving beyond just batch analytics on historical data. BigQuery aims to provide fast queries on massive datasets.

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 52

Knowledge Hut

JULY 26, 2023

Consider exploring relevant Big Data Certification to deepen your knowledge and skills. What is Big Data? Big Data is the term used to describe extraordinarily massive and complicated datasets that are difficult to manage, handle, or analyze using conventional data processing methods.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Knowledge Hut

JULY 28, 2023

Data Requirements ML models typically require more labelled training data to achieve good performance. DL models can learn from large amounts of labelled or unlabelled data, potentially reducing the need for extensive labelled datasets.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

ProjectPro

NOVEMBER 17, 2021

Instead, working on a sentiment analysis project with real datasets will help you stand out in job applications and improve your chances of receiving a call back from your dream company. The dataset for Amazon Product Reviews: Amazon Product Reviews Dataset. Beginners can use the small IMDb reviews dataset to test their skills.

Coding 52

Coding Project Entertainment Datasets 52

Rockset

AUGUST 11, 2020

The recommendation models improved engagement when the models had access to more recent actions of its users. Data that used to be batch-loaded daily into Hadoop for model serving started to get loaded continuously, at first hourly and then in fifteen minutes intervals. Why is that?

Hadoop 52

Hadoop Datasets Banking Analytics Application 52

phData: Data Engineering

SEPTEMBER 19, 2023

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Edureka

AUGUST 2, 2023

Python offers a strong ecosystem for data scientists to carry out activities like data cleansing, exploration, visualization, and modeling thanks to modules like NumPy, Pandas, and Matplotlib. Data scientists use SQL to query, update, and manipulate data.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Rockset

JUNE 12, 2023

Amazon DynamoDB’s flexible schema makes it easy to store and retrieve data in a variety of formats, which is particularly useful for Clinical ink’s application that requires handling dynamic, semi-structured data. We ran two tests using queries with different levels of complexity: Query 1: Simple query on a few fields of data.

Electronics 52

Electronics Datasets Bytes Architecture 52

ProjectPro

NOVEMBER 25, 2021

Although businesses have an inclination towards structured data for insight generation and decision-making, text data is one of the vital information generated from digital platforms. However, it is not straightforward to extract or derive insights from a colossal amount of text data.

Machine Learning 52

Machine Learning Algorithm Datasets Google Cloud 52

ProjectPro

SEPTEMBER 29, 2021

Machine learning uses algorithms that teach machines to learn and improve with data without explicit programming automatically. Image Credit: Twitter Get FREE Access to Machine Learning Example Codes for Data Cleaning, Data Munging, and Data Visualization Is NLP considered Machine Learning?

Machine Learning 52

Machine Learning Deep Learning Algorithm Datasets 52

Rockset

SEPTEMBER 20, 2022

However, analyzing the data generated on the blockchain by these dApps is challenging. The appeal of blockchain - namely, open access, permissionless access, privacy and transparency - renders the on-chain data relatively basic, with only simple transaction details recorded.

PostgreSQL 52

PostgreSQL MongoDB SQL Datasets 52

Knowledge Hut

DECEMBER 26, 2023

Mining of Massive Datasets By Jure Leskovec, Anand Rajaraman, Jeff Ullma This book will provide a comprehensive understanding of large-scale data mining and network analysis. Some other features that make it a book ideal for advanced learners are as follows:- This book will help you learn how to mine significantly large datasets.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

ProjectPro

OCTOBER 18, 2021

Datasets like Google Local, Amazon product reviews, MovieLens, Goodreads, NES, Librarything are preferable for creating recommendation engines using machine learning models. They have a well-researched collection of data such as ratings, reviews, timestamps, price, category information, customer likes, and dislikes.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52