Knowledge Hut

APRIL 25, 2023

An end-to-end Data Science pipeline starts from business discussion to delivering the product to the customers. One of the key components of this pipeline is Data ingestion. It helps in integrating data from multiple sources such as IoT, SaaS, on-premises, etc., What is Data Ingestion?

Data Ingestion 52

Data Ingestion Lambda Architecture Raw Data Data Science 52

Pinterest Engineering

APRIL 7, 2025

For these use cases, typically datasets are generated offline in batch jobs and get bulk uploaded from S3 to the database running on EC2. In the case during the instance migration, even though the measured network throughput was well below the baseline bandwidth, we still see TCP retransmits to spike during bulk data ingestion into EC2.

AWS 53

AWS Bytes Database Data Ingestion 53

Cloudera

MAY 19, 2021

To try and predict this, an extensive dataset including anonymised details on the individual loanee and their historical credit history are included. As a machine learning problem, it is a classification task with tabular data, a perfect fit for RAPIDS. Get the Dataset. The dataset can be downloaded from: [link].

Machine Learning 137

Machine Learning Data Science Datasets Raw Data 137

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?

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Cloudera

AUGUST 26, 2021

In addition to big data workloads, Ozone is also fully integrated with authorization and data governance providers namely Apache Ranger & Apache Atlas in the CDP stack. While we walk through the steps one by one from data ingestion to analysis, we will also demonstrate how Ozone can serve as an ‘S3’ compatible object store.

Data Science 113

Data Science Cloud Hadoop Metadata 113

Ascend.io

OCTOBER 28, 2024

Filling in missing values could involve leveraging other company data sources or even third-party datasets. The cleaned data would then be stored in a centralized database, ready for further analysis. This ensures that the sales data is accurate, reliable, and ready for meaningful analysis.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Rockset

MAY 3, 2023

lower latency than Elasticsearch for streaming data ingestion. We’ll also delve under the hood of the two databases to better understand why their performance differs when it comes to search and analytics on high-velocity data streams. Why measure streaming data ingestion? Data Latency: Rockset sees up to 2.5x

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Snowflake

APRIL 18, 2024

Legacy SIEM cost factors to keep in mind Data ingestion: Traditional SIEMs often impose limits to data ingestion and data retention. Snowflake allows security teams to store all their data in a single platform and maintain it all in a readily accessible state, with virtually unlimited cloud data storage capacity.

Data Lake 109

Data Lake Data Ingestion Bytes Cloud Computing 109

Lyft Engineering

NOVEMBER 29, 2023

Druid at Lyft Apache Druid is an in-memory, columnar, distributed, open-source data store designed for sub-second queries on real-time and historical data. Druid enables low latency (real-time) data ingestion, flexible data exploration and fast data aggregation resulting in sub-second query latencies.

Kafka 106

Kafka Data Ingestion Architecture Datasets 106

Data Engineering Weekly

JULY 7, 2024

Experience Enterprise-Grade Apache Airflow Astro augments Airflow with enterprise-grade features to enhance productivity, meet scalability and availability demands across your data pipelines, and more. Hudi seems to be a de facto choice for CDC data lake features. Notion migrated the insert heavy workload from Snowflake to Hudi.

Data Engineer 98

Data Engineer Data Engineering Engineering Data Lake 98

Pinterest Engineering

SEPTEMBER 12, 2023

transformers) became standardized, ML engineers started to show a growing appetite to iterate on datasets. While such dataset iterations can yield significant gains, we observed that only a handful of such experiments were conducted and productionized in the last six months. As model architecture building blocks (e.g.

Data Process 105

Data Process Process Datasets Software Engineering 105

Cloudera

OCTOBER 11, 2021

Modak’s Nabu is a born in the cloud, cloud-neutral integrated data engineering platform designed to accelerate the journey of enterprises to the cloud. The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata.

Data Engineer 95

Data Engineer Data Engineering Cloud Engineering 95

Cloudera

AUGUST 17, 2022

Only data platform with built-in capability to ingest data from on-prem to the cloud. Readily Accessible Data Ingestion and Analytics. Sophisticated data practitioners and business analysts want access to new datasets that can help optimize their work and transform whole business functions.

Cloud Computing 116

Cloud Computing Cloud Storage Data Science Machine Learning 116

Cloudera

DECEMBER 14, 2021

So to improve the speed of data analysis, the IRS worked with the combined technology integrating Cloudera Data Platform (CDP) and NVIDIA’s RAPIDS Accelerator for Apache Spark 3.0. The Roads and Transport Authority (RTA) operating in Dubai wanted to apply big data capabilities to transportation and enhance travel efficiency.

Transportation 111

Transportation Telecommunication Banking Data Lake 111

Towards Data Science

FEBRUARY 16, 2024

As we are pulling data with discrepancies together from different operational systems, the data ingestion process can be more time-consuming than originally thought! Including basic data cleaning and manual mapping as the first step can improve data consistency and alignment for more accurate results.

Food 94

Food Data Ingestion Python Data Science 94

Cloudera

JANUARY 20, 2021

The data journey is not linear, but it is an infinite loop data lifecycle – initiating at the edge, weaving through a data platform, and resulting in business imperative insights applied to real business-critical problems that result in new data-led initiatives. Conclusion.

Manufacturing 110

Manufacturing Data Warehouse Kafka Retail 110

Cloudera

NOVEMBER 17, 2020

Once the prototype has been completely deployed, you will have an application that is able to make predictions to classify transactions as fraudulent or not: The data for this is the widely used credit card fraud dataset. Data analysis – create a plan to build the model.

Deep Learning 115

Deep Learning Machine Learning Raw Data Data Ingestion 115

Data Engineering Podcast

JULY 3, 2022

Random data doesn’t do it — and production data is not safe (or legal) for developers to use. What if you could mimic your entire production database to create a realistic dataset with zero sensitive data? Random data doesn’t do it — and production data is not safe (or legal) for developers to use.

Data Integration 100

Data Integration MongoDB MySQL Scala 100

Striim

SEPTEMBER 11, 2024

Data Collection/Ingestion The next component in the data pipeline is the ingestion layer, which is responsible for collecting and bringing data into the pipeline. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Confluent

FEBRUARY 6, 2019

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. The use case is fraud detection for credit card payments.

Machine Learning 107

Machine Learning Python Kafka Java 107

Cloudera

FEBRUARY 8, 2021

ECC will enrich the data collected and will make it available to be used in analysis and model creation later in the data lifecycle. Below is the entire set of steps in the data lifecycle, and each step in the lifecycle will be supported by a dedicated blog post(see Fig.

Data Pipeline 118

Data Pipeline Building Manufacturing Data Warehouse 118

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. ® , Go, and Python SDKs where an application can use SQL to query raw data coming from Kafka through an API (but that is a topic for another blog). In addition, it is often used for smaller datasets (e.g.,

Kafka 21

Kafka SQL BI Hadoop 21

Data Engineering Podcast

JUNE 26, 2022

Random data doesn’t do it — and production data is not safe (or legal) for developers to use. What if you could mimic your entire production database to create a realistic dataset with zero sensitive data? Random data doesn’t do it — and production data is not safe (or legal) for developers to use.

Data Management 100

Data Management Management MongoDB MySQL 100

Data Engineering Weekly

SEPTEMBER 18, 2024

Data testing checks for rule-based validations, while observability ensures overall pipeline health, tracking aspects like latency, freshness, and lineage. How to Evaluate a Data Observability Tool When selecting a data observability tool, assessing both functionality and how well it integrates into your existing data stack is important.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Data 98

Towards Data Science

MARCH 2, 2024

The primary objective here is to establish a metric that can effectively measure the cleanliness level of a dataset, translating this concept into a concrete optimisation problem. or HoloClean: Holistic Data Repairs with Probabilistic Inference ). Data issues should be locateable to specific cells.

Datasets 92

Datasets Data Data Science Python 92

Towards Data Science

JULY 8, 2024

Williams on Unsplash Data pre-processing is one of the major steps in any Machine Learning pipeline. Tensorflow Transform helps us achieve it in a distributed environment over a huge dataset. ML Pipeline operations begins with data ingestion and validation, followed by transformation. You can access it from here.

Data Preparation 70

Data Preparation Datasets Metadata Data Ingestion 70

Towards Data Science

NOVEMBER 16, 2023

Data Management A tutorial on how to use VDK to perform batch data processing Photo by Mika Baumeister on Unsplash Versatile Data Ki t (VDK) is an open-source data ingestion and processing framework designed to simplify data management complexities.

Data Process 98

Data Process Process Raw Data Data 98

Towards Data Science

NOVEMBER 4, 2023

Indeed, datalakes can store all types of data including unstructured ones and we still need to be able to analyse these datasets. Indeed, why would we build a data connector from scratch if it already exists and is being managed in the cloud? You can change these # to conform to your data. Datalake example.

Data Engineer 98

Data Engineer Data Engineering Engineering BI 98

Data Engineering Podcast

MAY 29, 2022

With Select Star’s data catalog, a single source of truth for your data is built in minutes, even across thousands of datasets. report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. You’ll also get a swag package when you continue on a paid plan.

Database 100

Database Architecture Data Architecture PostgreSQL 100

Data Engineering Podcast

JULY 31, 2022

Summary Exploratory data analysis works best when the feedback loop is fast and iterative. This is easy to achieve when you are working on small datasets, but as they scale up beyond what can fit on a single machine those short iterations quickly become long and tedious. In fact, while only 3.5% That’s where our friends at Ascend.io

Data Analysis 100

Data Analysis MongoDB Algorithm MySQL 100

Confluent

JULY 3, 2019

Twitter represents the default source for most event streaming examples, and it’s particularly useful in our case because it contains high-volume event streaming data with easily identifiable keywords that can be used to filter for relevant topics. Ingesting Twitter data. wwc : defines the BigQuery dataset name.

Data Analysis 21

Data Analysis Kafka Datasets Java 21

DataKitchen

MAY 10, 2024

This use case is vital for organizations that rely on accurate data to drive business operations and strategic decisions. Data Ingestion Continuous monitoring during data ingestion ensures that updates to existing data sources are accurate and consistent.

Data Ingestion 56

Data Ingestion Datasets Data Coding 56

LinkedIn Engineering

DECEMBER 20, 2023

In content moderation classifier development, there are Data ETL (Export, Transform, Load) pipelines that collect data from various sources and store it in offline locations like a data lake or HDFS. Most of these steps are automated using the AutoML framework, saving data scientists’ time and reducing the risk of errors.

Machine Learning 90

Machine Learning Datasets Algorithm Architecture 90

Netflix Tech

MARCH 25, 2019

As a result, a single consolidated and centralized source of truth does not exist that can be leveraged to derive data lineage truth. Therefore, the ingestion approach for data lineage is designed to work with many disparate data sources. push or pull. Today, we are operating using a pull-heavy model.

Building 90

Building Metadata Transportation Data Ingestion 90

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Effective Data Anomaly Monitoring (#2) Introduction Ensuring the accuracy and timeliness of data ingestion is a cornerstone for maintaining the integrity of data systems. This process is critical as it ensures data quality from the onset.

Data Ingestion 52

Data Ingestion Transportation High Quality Data Data 52

Knowledge Hut

JUNE 26, 2023

Since there are numerous ways to approach this task, it encourages originality in one's approach to data analysis. Moreover, this project concept should highlight the fact that there are many interesting datasets already available on services like GCP and AWS. Source: Use Stack Overflow Data for Analytic Purposes 4.

Data Engineer 98

Data Engineer Data Engineering Coding Project 98