AltexSoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. High latency of data access. No real-time data processing.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Striim

SEPTEMBER 11, 2024

Understanding the essential components of data pipelines is crucial for designing efficient and effective data architectures. In an ETL-based architecture, data is first extracted from source systems, then transformed into a structured format, and finally loaded into data stores, typically data warehouses.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Netflix Tech

OCTOBER 27, 2020

Netflix Scheduler is built on top of Meson which is a general purpose workflow orchestration and scheduling framework to execute and manage the lifecycle of the data workflow. Bulldozer makes data warehouse tables more accessible to different microservices and reduces each individual team’s burden to build their own solutions.

Data Warehouse 100

Data Warehouse Datasets Data Big Data 100

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

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 92

Data Analysis PostgreSQL Data Science Machine Learning 92

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes.

Systems 80

Systems Building Management Data Lake 80

Edureka

FEBRUARY 13, 2025

Prerequisites Before you begin with few-shot learning, make sure you have the following: Access to a High-Powered GPU: Use a strong NVIDIA GPU, like the H100 or A100-80G, to run deep learning models effectively. Access to Cloud-Based Resources (Optional): If you don’t have a powerful GPU, you might want to use cloud services.

Deep Learning 52

Deep Learning Datasets Data Machine Learning 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 97

Data Pipeline Coding Raw Data Accessible 97

Edureka

JUNE 7, 2024

paintings, songs, code) Historical data relevant to the prediction task (e.g., Generative AI leverages the power of deep learning to build complex statistical models that process and mimic the structures present in different types of data.

Deep Learning 114

Deep Learning Media Algorithm Manufacturing 114

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 Engineer 98

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 98

Data Governance Government Generalist Data Engineer 98

Monte Carlo

MARCH 12, 2025

Lesson 5: Splitting tasks horizontally reduces runtime Lets say we have two tasks we want to perform (pink and blue) on a large dataset. For example, when theres an issue, only the ML, BE, or engineers have access to the AI stack, system, and logs to understand the issue, and only the data scientists have the expertise to actually solve it.

AWS 52

AWS Google Cloud Unstructured Data Coding 52

Monte Carlo

MARCH 12, 2025

Lesson 5: Splitting tasks horizontally reduces runtime Lets say we have two tasks we want to perform (pink and blue) on a large dataset. For example, when theres an issue, only the ML, BE, or engineers have access to the AI stack, system, and logs to understand the issue, and only the data scientists have the expertise to actually solve it.

AWS 52

AWS Google Cloud Unstructured Data Coding 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 Machine Learning Business Intelligence 97

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Volume Big Data refers to large volumes of data, typically in the order of terabytes or petabytes. It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques.

Big Data 52

Big Data Datasets Data Analysis Media 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. Also, storage is much cheaper than compute and that means: With pre-joined datasets, you exchange compute for storage resources!

Bytes 97

Bytes Google Cloud Cloud Storage Utilities 97

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. link] Daniel Beach: Delta Lake - Map and Array data types Having a well-structured data model is always great, but we often handle semi-structured data.

Data Engineer 67

Data Engineer Data Engineering Engineering Google Cloud 67

Knowledge Hut

APRIL 23, 2024

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Data warehousing offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 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 Engineer 70

Data Engineer Data Engineering Engineering Unstructured Data 70

Edureka

MARCH 26, 2025

No Transformation: The input layer only passes data on to the hidden layer below; it does not process or alter the data in any way. Dimensionality: The number of characteristics in the dataset is directly proportional to the number of neurons in the input layer. How are neural networks used in AI? Is GAN a neural network?

Raw Data 40

Raw Data Architecture Deep Learning Finance 40

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 Structured Data 52

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

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Specification of access conditions for specific users and groups.

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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? This is a good approach as it allows less space for error.

Big Data 52

Big Data Relational Database Data Structured Data 52

Confluent

AUGUST 29, 2019

In an identity/access management application, it’s the relationships between roles and their privileges that matters most. If you’ve found yourself needing to write very large JOIN statements or dealing with long paths through your data, then you are probably facing a graph problem. Relationships act like verbs in your graph.

Kafka 55

Kafka Process Algorithm Cloud 55

Knowledge Hut

MAY 3, 2024

Perform iteration with enumerate() instead of range() Consider a situation during a coding interview: You have a list of elements, and you have to iterate over the list with the access to both the indices and values. Replace all integers divisible by 5 with “buzz”. Replace all integers divisible by 3 and 5 with “fizzbuzz”.

Python 98

Python Coding Data Programming 98

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. What is Big Data analytics?

Big Data 78

Big Data Data Analytics IT NoSQL 78

Edureka

JULY 4, 2024

Overwhelmed with log files and sensor data? It is a cloud-based service by Amazon Web Services (AWS) that simplifies processing large, distributed datasets using popular open-source frameworks, including Apache Hadoop and Spark. Businesses can run these workflows on a recurring basis, which keeps data fresh and analysis-ready.

AWS 52

AWS Amazon Web Services Hadoop Big Data 52

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 Raw Data 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 Banking Datasets Analytics Application 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

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics. No wonder only 0.5

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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

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

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 Engineer 52

Data Engineer Data Engineering Engineering Datasets 52

ProjectPro

JANUARY 25, 2022

Furthermore, PySpark allows you to interact with Resilient Distributed Datasets (RDDs) in Apache Spark and Python. Because of its interoperability, it is the best framework for processing large datasets. Easy Processing- PySpark enables us to process data rapidly, around 100 times quicker in memory and ten times faster on storage.

Big Data 52

Big Data Data Process Process Kafka 52