Data Engineering Podcast

MAY 26, 2024

When that system is responsible for the data layer the process becomes more challenging. Sriram Panyam has been involved in several projects that required migration of large volumes of data in high traffic environments. Can you start by sharing some of your experiences with data migration projects?

Systems 130

Systems Data Lake High Quality Data Google Cloud 130

Precisely

APRIL 11, 2023

It’s a common scenario across industries: a new strategic initiative is launching, and you need trustworthy, relevant data to analyze and support the best outcomes for the business. Let’s explore some of the questions you must ask as you begin the process, then dive into the solutions for common challenges you may face.

Accessible 52

Accessible Accessibility Metadata Data Integration 52

Knowledge Hut

JANUARY 18, 2024

“Big data Analytics” is a phrase that was coined to refer to amounts of datasets that are so large traditional data processing software simply can’t manage them. For example, big data is used to pick out trends in economics, and those trends and patterns are used to predict what will happen in the future.

Data Process 52

Data Process Process Hadoop Scala 52

Robinhood

FEBRUARY 7, 2024

Robinhood was founded on a simple idea: that our financial markets should be accessible to all. With customers at the heart of our decisions, Robinhood is lowering barriers and providing greater access to financial information and investing. from Robinhood Data Infrastructure Robinhood adheres to a data-first philosophy. .

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Process Hadoop Architecture Accessible 75

Ascend.io

MAY 23, 2023

The data engineering world is full of tips and tricks on how to handle specific patterns that recur with every data pipeline. A prime example of such patterns is orphaned datasets. Typically, these orphaned datasets are addressed with ad-hoc manual protocols and after-the-fact garbage collection processes.

Datasets 52

Datasets Data Pipeline Metadata Database 52

Analytics Vidhya

FEBRUARY 6, 2023

Introduction HDFS (Hadoop Distributed File System) is not a traditional database but a distributed file system designed to store and process big data. It is a core component of the Apache Hadoop ecosystem and allows for storing and processing large datasets across multiple commodity servers.

Data Storage 185

Data Storage Big Data Hadoop Datasets 185

Towards Data Science

MARCH 29, 2023

Turbo and GPT-4 for Predicting Humanitarian Data Categories Image created by Stable Diffusion with prompt ‘Predicting Cats’. Turbo and GPT-4 to categorize datasets without the need for labeled data or model training, by prompting the model with data excerpts and category definitions. Using GPT-3.5-Turbo

Datasets 61

Datasets Food Retail Hospitality 61

Knowledge Hut

JULY 28, 2023

Data Labeling is the process of assigning meaningful tags or annotations to raw data, typically in the form of text, images, audio, or video. These labels provide context and meaning to the data, enabling machine learning algorithms to learn and make predictions. What is Data Labeling for Machine Learning?

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Machine Learning Process Datasets Raw Data 52

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. What Does a Data Processing Analyst Do?

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Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

FEBRUARY 29, 2024

Being a data scientist means constantly growing, enabling businesses to become more data-propelled, and learning newer trends and tools. There are various excellent resources in data science that can help you to develop your skillset. So, having the right knowledge of tools and technology is important for handling such data.

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Data Science Datasets Database Design Machine Learning 98

AltexSoft

OCTOBER 18, 2022

Everyday the global healthcare system generates tons of medical data that — at least, theoretically — could be used for machine learning purposes. Regardless of industry, data is considered a valuable resource that helps companies outperform their rivals, and healthcare is not an exception. Medical data labeling. Let’s sum up.

Medical 52

Medical Datasets Machine Learning Hospitality 52

Knowledge Hut

APRIL 23, 2024

In today's data-driven world, the volume and variety of information are growing unprecedentedly. As organizations strive to gain valuable insights and make informed decisions, two contrasting approaches to data analysis have emerged, Big Data vs Small Data.

Big Data 52

Big Data Datasets Data Analysis Media 52

Engineering at Meta

MAY 22, 2024

In recent years, Meta’s data management systems have evolved into a composable architecture that creates interoperability, promotes reusability, and improves engineering efficiency. Data is at the core of every product and service at Meta. We needed to change our thinking to be able to move faster.

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Data Management Management Data SQL 93

Christophe Blefari

APRIL 14, 2023

Anyway, here the weekly Data News, written faster than usual. Hot takes on the Modern Data Stack — Matt gives 5 hot takes about the MDS. This time he writes about the new marketing approach of the modern data stack ecosystem. Data Economy 💰 Cybersyn raises $62.9m

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Datasets Data Deep Learning SQL 130

Knowledge Hut

MARCH 22, 2024

Reverse engineering software is the process of dissecting it to understand its components, functionality, and workflow without having access to the source code. Reverse engineering can help recover or migrate data to more modern systems, ensuring that no critical information is lost. Where is Reverse Engineering Used?

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Process Engineering Electronics Software Engineer 52

Knowledge Hut

APRIL 19, 2023

The process of gathering and compiling data from various sources is known as data Aggregation. Businesses and groups gather enormous amounts of data from a variety of sources, including social media, customer databases, transactional systems, and many more. Aggregation of data is useful in this situation.

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Process Data Mining Aggregated Data Portfolio 59

Striim

NOVEMBER 17, 2023

In today’s data-driven world, the ability to leverage real-time data for machine learning applications is a game-changer. Real-time data processing in the world of machine learning allows data scientists and engineers to focus on model development and monitoring.

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Databand.ai

JULY 6, 2023

Data Integrity Testing: Goals, Process, and Best Practices Niv Sluzki July 6, 2023 What Is Data Integrity Testing? Data integrity testing refers to the process of validating the accuracy, consistency, and reliability of data stored in databases, data warehouses, or other data storage systems.

Data Integration 52

Data Integration Process Data Validation Data Governance 52

Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. In this article: Why Is Data Ingestion Important?

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Data Ingestion Process Data Cleanse Data Governance 52

AltexSoft

AUGUST 25, 2021

And this technology of Natural Language Processing is available to all businesses. Available methods for text processing and which one to choose. Specifics of data used in NLP. What is Natural Language Processing? Here are some big text processing types and how they can be applied in real life. Main NLP use cases.

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Process Deep Learning Datasets Machine Learning 139

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.

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Big Data Media Datasets Unstructured Data 52

Christophe Blefari

SEPTEMBER 28, 2023

Make your data stack take-off ( credits ) Hello, another edition of Data News. This week, we're going to take a step back and look at the current state of data platforms. What are the current trends and why are people fighting around the concept of the modern data stack. Is the modern data stack dying?

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Cloud Storage Big Data Hadoop SQL 147

Towards Data Science

NOVEMBER 4, 2023

Platform Specific Tools and Advanced Techniques Photo by Christopher Burns on Unsplash The modern data ecosystem keeps evolving and new data tools emerge now and then. In this article, I want to talk about crucial things that affect data engineers. Are your data pipelines efficient? Data warehouse exmaple.

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Data Engineering Data Engineer Engineering BI 79

Knowledge Hut

JUNE 10, 2024

As a seasoned data scientist, I understand the pivotal role data plays in our field. Handling vast amounts of data is essential for maximizing career opportunities. The exponential growth of data, with 55-65 percent being unstructured, as reported by Forbes.com, poses significant challenges for analysis.

Data Science 52

Data Science Python Deep Learning Machine Learning 52

Tweag

APRIL 19, 2023

The MedTech industry is buzzing thanks to a continuous stream of innovation, promising to be more precise, efficient and accessible than ever. To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. OpenSlide test data: CMU-1.tiff

Medical 59

Medical Process Cloud Bytes 59

Databand.ai

MAY 30, 2023

6 Pillars of Data Quality and How to Improve Your Data Eric Jones May 30, 2023 What Is Data Quality? Data quality refers to the degree of accuracy, consistency, completeness, reliability, and relevance of the data collected, stored, and used within an organization or a specific context.

Data Cleanse 85

Data Cleanse Datasets Data Governance Data Validation 85

Knowledge Hut

JULY 24, 2023

The future of SQL (Structured Query Language) is a scalding subject among professionals in the data-driven world. As data generation continues to skyrocket, the demand for real-time decision-making, data processing, and analysis increases. According to recent studies, the global database market will grow from USD 63.4

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Database SQL Process NoSQL 52

Knowledge Hut

MAY 21, 2024

It would be helpful to know which laptops are most suited for your needs if you're a data scientist looking for the perfect one for your work. You have several options, but which is the best laptop for data science that satisfies all of your needs and demands? HP Envy 17T is a laptop designed for all your data science needs.

Data Science 98

Data Science Datasets Algorithm Electronics 98

Engineering at Meta

FEBRUARY 20, 2024

We’ve partnered with Voltron Data and the Arrow community to align and converge Apache Arrow with Velox , Meta’s open source execution engine. This new convergence helps Meta and the larger community build data management systems that are unified, more efficient, and composable.

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Data Management Bytes Management Datasets 103

ProjectPro

JANUARY 25, 2022

Did you know that, according to Linkedin, over 24,000 Big Data jobs in the US list Apache Spark as a required skill? Learning Spark has become more of a necessity to enter the Big Data industry. Python is one of the most extensively used programming languages for Data Analysis, Machine Learning , and data science tasks.

Big Data 52

Big Data Data Process Process Kafka 52

Precisely

MAY 16, 2024

Key takeaways: The success of your AI initiatives hinges on the integrity of your data. Ensure your data is accurate, consistent, and contextualized to enable trustworthy AI systems that avoid biases, improve accuracy and reliability, and boost contextual relevance and nuance. Why Does Data Integrity Matter for AI Success?

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Amazon Web Services AWS Data Integration Datasets 69

Towards Data Science

FEBRUARY 6, 2024

ERP and CRM systems are designed and built to fulfil a broad range of business processes and functions. This generalisation makes their data models complex and cryptic and require domain expertise. Searching for data Imagine being a data engineer/analyst tasked with identifying the top-selling products within your company.

Systems 76

Systems Raw Data Metadata Data Cleanse 76

Towards Data Science

OCTOBER 21, 2023

Efficient geospatial manipulations for OSM map data Photo by Tabea Schimpf on Unsplash If you’ve worked with OSM data before, you know it’s not the easiest to extract. OSM data can be huge, and finding performant solutions for what you want to analyze is often a challenge. Let’s get into what this library can do! ?

Datasets 72

Datasets Data Data Science Python 72

Ascend.io

FEBRUARY 15, 2024

A common hurdle that many data engineering teams face is how to choose the right data replication strategy. This article breaks down the complexities of data replication strategies in a way that’s easy to understand. That can include the creation of historical data that is not available in the source system.

Datasets 52

Datasets Database Data Warehouse Data 52

Knowledge Hut

JANUARY 3, 2024

In today’s age, a lot of data is being generated daily. Analyzing these data for certain patterns and trends in the raw format is challenging. Here’s how data visualization comes into play. How To Use Python For Data Visualization? Python libraries for data visualization are designed with their specifications.

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Python Programming Language Datasets R (Programming) 98

Towards Data Science

JANUARY 7, 2024

Streamline Data Pipelines: How to Use WhyLogs with PySpark for Effective Data Profiling and Validation Photo by Evan Dennis on Unsplash Data pipelines, made by data engineers or machine learning engineers, do more than just prepare data for reports or training models. It lets you log all sorts of data.

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Data Pipeline Hospitality Data Validation Datasets 74