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 Schemas 52

Rockset

MARCH 1, 2023

When you deconstruct the core database architecture, deep in the heart of it you will find a single component that is performing two distinct competing functions: real-time data ingestion and query serving. When data ingestion has a flash flood moment, your queries will slow down or time out making your application flaky.

Data Ingestion 144

Data Ingestion Database Architecture Cloud Storage 144

DataKitchen

MAY 10, 2024

This initial stage of data observability ensures that data quality is maintained from the start, preventing errors that could affect downstream processes and decisions. This use case is vital for organizations that rely on accurate data to drive business operations and strategic decisions.

Data Ingestion 56

Data Ingestion Datasets Data Coding 56

phData: Data Engineering

SEPTEMBER 19, 2023

Data lakes have emerged as a popular solution, offering the flexibility to store and analyze diverse data types in their raw format. However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Consistency of data throughout the data lake.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

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

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. Big data offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Christophe Blefari

OCTOBER 14, 2023

A microservice approach for DAG authoring using datasets — The idea is to apply SE patterns to pipelines like migration , broadcast and aggregate. In addition you should create micropipelines which we can define as small, loosely coupled DAG which operates on one input Dataset and produces one output Dataset.

Python 130

Python Datasets Data Data Ingestion 130

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs. Have I Checked The Raw Data And The Integrated Data?

Raw Data 49

Raw Data Data Ingestion Datasets Data 49

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 104

Kafka Data Ingestion Datasets Architecture 104

DataKitchen

MAY 10, 2024

The Fourth of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Data Ingestion 49

Data Ingestion Datasets Coding Data 49

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 80

Data Lake Data Ingestion Bytes Cloud Computing 80

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 62

Food Data Ingestion Python Data Science 62

Ascend.io

AUGUST 15, 2023

While terms like “Fivetran ETL” or “Fivetran data pipeline” are echoing in the corridors of data professionals, the truth is, Fivetran is primarily an expert on data ingestion — just the first step in a much broader and nuanced data management process.

Data Management 52

Data Management Management Data Ingestion Data Pipeline 52

Rockset

JANUARY 30, 2024

The memory optimized instance class is ideal for queries that process large datasets or have a large working set size due to the mix of queries. This is not a hands-free operation and also involves the transfer of data across nodes. Microbatching Rockset is known for its low-latency streaming data ingestion and indexing.

Data Ingestion 64

Data Ingestion Utilities Architecture SQL 64

ProjectPro

JANUARY 25, 2022

Furthermore, PySpark allows you to interact with Resilient Distributed Datasets (RDDs) in Apache Spark and Python. PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. You can accomplish this using the Py4j library.

Big Data 52

Big Data Data Process Process Kafka 52

DataKitchen

MAY 10, 2024

The First of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Data Cleanse 49

Data Cleanse Data Ingestion Data Datasets 49

Data Engineering Weekly

MARCH 24, 2024

As we predicted in the key trends of 2023 about Apache Flink as a clear winner in the stream processing frameworks, we see Confluent offering Flink as a service. The author goes beyond comparing the tools to various offerings from streaming vendors in stream processing and Kafka protocol-supported systems.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

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

LinkedIn Engineering

DECEMBER 20, 2023

Automated Machine Learning (AutoML) refers to a framework or platform that automates the entire machine learning process. Leveraging AutoML, we transformed what used to be a lengthy and intricate process into one which is both streamlined and efficient. What is AutoML?

Machine Learning 90

Machine Learning Datasets Algorithm Architecture 90

Cloudera

MAY 19, 2021

This year, we expanded our partnership with NVIDIA , enabling your data teams to dramatically speed up compute processes for data engineering and data science workloads with no code changes using RAPIDS AI. As a machine learning problem, it is a classification task with tabular data, a perfect fit for RAPIDS.

Machine Learning 137

Machine Learning Datasets Data Science Raw Data 137

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 111

Data Science Cloud Hadoop Metadata 111

FreshBI

SEPTEMBER 11, 2023

Power BI, Microsoft's cutting-edge business analytics solution, empowers users to visualize data and seamlessly distribute insights. However, the complex process of data preparation, modeling, and report creation can be time and resource consuming, especially when handling intricate datasets.

BI 59

BI Consulting Datasets Data Ingestion 59

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Ingestion 40

Data Ingestion Data Government Datasets 40

Data Engineering Podcast

JULY 3, 2022

Summary The perennial challenge of data engineers is ensuring that information is integrated reliably. While it is straightforward to know whether a synchronization process succeeded, it is not always clear whether every record was copied correctly. Can you describe what the data diff tool is and the story behind it?

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Cloudyard

APRIL 4, 2024

However, the volume of daily transaction data poses challenges in effectively segmenting customers and optimizing engagement. This blog post explores how Snowpark, a powerful tool for data processing within Snowflake, can be used to perform RFM segmentation and unlock actionable customer insights.

Retail 40

Retail Data Ingestion Metadata Datasets 40

Ascend.io

JUNE 8, 2023

Acting as the core infrastructure, data pipelines include the crucial steps of data ingestion, transformation, and sharing. Data Ingestion Data in today’s businesses come from an array of sources, including various clouds, APIs, warehouses, and applications.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

ProjectPro

FEBRUARY 6, 2023

With over 10 million active subscriptions, 50 million active topics, and a trillion messages processed per day, Google Cloud Pub/Sub makes it easy to build and manage complex event-driven systems. Google Cloud Pub/Sub is a global, cloud-based messaging framework that has become increasingly popular among data engineers over recent years.

Google Cloud 52

Google Cloud Cloud Cloud Storage Data Ingestion 52

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 60

Datasets Data Data Science Python 60

Confluent

FEBRUARY 21, 2019

By taking data from a tool such as Sysmon and streaming it into Kafka for processing in KSQL, you can rapidly detect suspicious behavior by looking for a process spawning a new process that makes an external network connection. This is because the Create method allows a user to create a process either locally or remotely.

Process 80

Process Kafka Datasets SQL 80

Towards Data Science

NOVEMBER 4, 2023

The data engineering landscape is constantly changing but major trends seem to remain the same. How to Become a Data Engineer As a data engineer, I am tasked to design efficient data processes almost every day. It was created by Spotify to manage massive data processing workloads. Datalake example.

Data Engineering 82

Data Engineering Data Engineer Engineering BI 82

Ascend.io

MAY 31, 2023

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Table of Contents The Common Threads: Ingest, Transform, Share Before we explore the differences between the ETL process and a data pipeline , let’s acknowledge their shared DNA.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

Data Engineering Podcast

JUNE 26, 2022

Summary The most complicated part of data engineering is the effort involved in making the raw data fit into the narrative of the business. Master Data Management (MDM) is the process of building consensus around what the information actually means in the context of the business and then shaping the data to match those semantics.

Data Management 100

Data Management Management MongoDB Scala 100

Knowledge Hut

APRIL 23, 2024

The Emergence of Data Storage and Processing Technologies A data storage facility first appeared in the form of punch cards, developed by Basile Bouchon to facilitate pattern printing on textiles in looms. Herman Hollerith, a US Bureau employee, developed the analytical engine and strengthened its capacity to store data.

Big Data 52

Big Data Amazon Web Services Media Cloud Computing 52

Rockset

MAY 31, 2023

Understanding real-time workloads High QPS is often crucial for organizations that require real-time or near-real-time processing of a significant volume of queries. A database that serves real-time analytical queries has to process reads and writes concurrently. This is one reason why p95 query latencies are kept low.

Data Ingestion 52

Data Ingestion Datasets Architecture Retail 52

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 115

Cloud Computing Cloud Storage Data Science Government 115

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Engineering 92

Data Engineering Data Engineer Cloud Engineering 92

Ascend.io

AUGUST 29, 2023

Similarly , in data, every step of the pipeline, from data ingestion to delivery, plays a pivotal role in delivering impactful results. In this article, we’ll break down the intricacies of an end-to-end data pipeline and highlight its importance in today’s landscape.

Data Pipeline 52

Data Pipeline Pipeline-centric Database-centric Data Ingestion 52