Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Knowledge Hut

SEPTEMBER 29, 2023

This growth is creating a strong demand for data experts, especially Azure data engineers. But who are Azure data engineers, and what do they do? Moreover, what benefits can you expect from a career in Azure Data Engineering? Why Should You Get an Azure Data Engineer Certification?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudyard

APRIL 4, 2024

Read Time: 2 Minute, 13 Second Consider a scenario, you are part of data engineering team at a retail company. However, the volume of daily transaction data poses challenges in effectively segmenting customers and optimizing engagement. Traditional segmentation methods fall short in scalability and real-time insights.

Retail 40

Retail Data Ingestion Metadata Datasets 40

Netflix Tech

JANUARY 25, 2023

Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. For example, we have a service that stores a movie entity’s metadata or a service that stores metadata about images. In this case it is BOUNDING_BOX.

Algorithm 113

Algorithm Media Metadata Data Ingestion 113

phData: Data Engineering

SEPTEMBER 19, 2023

By employing robust data modeling techniques, businesses can unlock the true value of their data lake and transform it into a strategic asset. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

DataKitchen

OCTOBER 20, 2023

Example 2: The Data Engineering Team Has Many Small, Valuable Files Where They Need Individual Source File Tracking In a typical data processing workflow, tracking individual files as they progress through various stages—from file delivery to data ingestion—is crucial.

Insurance 67

Insurance Pharmaceutical Data Data Ingestion 67

LinkedIn Engineering

DECEMBER 12, 2023

Pinot is a columnar OLAP store that serves analytics queries on data ingested from realtime streams. PEDAL also consists of a metadata store that holds various algorithmic parameters, including the scale of noise that we introduce and whether we should use one-shot or continual observation algorithms.

Algorithm 77

Algorithm Metadata SQL Datasets 77

Netflix Tech

OCTOBER 19, 2020

a Netflix member via Twitter This is an example of a question our on-call engineers need to answer to help resolve a member issue?—?which In our previous blog post we introduced Edgar, our troubleshooting tool for streaming sessions. We needed to increase engineering productivity via distributed request tracing.

Building 93

Building Transportation Metadata Java 93

Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance.

Metadata 130

Metadata MongoDB Scala MySQL 130

Cloudera

FEBRUARY 16, 2022

We can think of model lineage as the specific combination of data and transformations on that data that create a model. This maps to the data collection, data engineering, model tuning and model training stages of the data science lifecycle. So, we have workspaces, projects and sessions in that order.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

Cloudera

AUGUST 31, 2021

It outperforms other data warehouses on all sizes and types of data, including structured and unstructured, while scaling cost-effectively past petabytes. Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. Consideration of both data & metadata in the migration.

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

RandomTrees

SEPTEMBER 6, 2020

Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS). Built on new SQL database engine, it provides a unique architecture designed for the cloud.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 69

Data Warehouse Cloud Kafka Cloud Storage 69

ProjectPro

AUGUST 24, 2021

Nevertheless, that is not the only job in the data world. Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. Accelerated Data Analytics DataOps tools help automate and streamline various data processes, leading to faster and more efficient data analytics.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Only metadata will be regenerated. Data quality using table rollback.

Cloud 76

Cloud Metadata Google Cloud Data Warehouse 76

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 82

Engineering Raw Data Data Science Scala 82

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Data Ingestion.

Machine Learning 136

Machine Learning Datasets Data Science Raw Data 136

LinkedIn Engineering

JUNE 15, 2023

In this blog post, we will discuss the AvroTensorDataset API, techniques we used to improve data processing speeds by up to 162x over existing solutions (thereby decreasing overall training time by up to 66%), and performance results from benchmarks and production. The bytes are decoded based on the provided features metadata (i.e.

Datasets 102

Datasets Bytes Process Data Ingestion 102

Netflix Tech

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. Some of the optimizations are prerequisites for a high-performance data warehouse. We can also reorganize the metadata to make file scanning much faster.

Data Warehouse 81

Data Warehouse Metadata Algorithm Data 81

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” Iceberg handles massive data born in the cloud.

Architecture 97

Architecture Metadata Unstructured Data Machine Learning 97

Netflix Tech

MARCH 25, 2019

Now, imagine yourself in the role of a software engineer responsible for a micro-service which publishes data consumed by few critical customer facing services (e.g. You are about to make structural changes to the data and want to know who and what downstream to your service will be impacted. push or pull.

Building 87

Building Metadata Transportation Data Ingestion 87

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

LinkedIn Engineering

JULY 27, 2023

Costwiz provides a unified experience that helps leaders drive more accurate forecasting of Azure budgets at LinkedIn with resource ownership detection, accountability, expedited remedies, and holistic data visibility (via custom dashboards). ETL processes must determine where to pick up the next batch of data.

Metadata 75

Metadata Utilities Cloud Data Lake 75

Cloudera

FEBRUARY 8, 2021

This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight. The first blog introduced a mock connected vehicle manufacturing company, The Electric Car Company (ECC), to illustrate the manufacturing data path through the data lifecycle.

Data Pipeline 114

Data Pipeline Building Manufacturing Data Warehouse 114

Cloudera

MARCH 31, 2021

Customers who have chosen Google Cloud as their cloud platform can now use CDP Public Cloud to create secure governed data lakes in their own cloud accounts and deliver security, compliance and metadata management across multiple compute clusters. Data Preparation (Apache Spark and Apache Hive) . Virtual Machines .

Google Cloud 90

Google Cloud Cloud Amazon Web Services Cloud Storage 90

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 84

Data Lake Business Intelligence Metadata Data Warehouse 84

Ascend.io

JUNE 8, 2023

However, transforming data into a product so that it can deliver outsized business value requires more than just a mission statement; it requires a solid foundation of technical capabilities and a truly data-centric culture. This multitude of sources often causes a dispersed, complex, and poorly structured data landscape.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream.

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Metadata in cluster is disjoint across components.

Pipeline-centric 98

Pipeline-centric Data Lake Hadoop Metadata 98

Rockset

JUNE 6, 2023

In this blog, we’ll walk through how Rockset provides compute-storage separation while making real-time data available to queries. Virtual instances (VIs) are allocations of compute and memory resources responsible for data ingestion, transformations, and queries.

Metadata 52

Metadata Datasets Architecture Algorithm 52

Cloudera

JUNE 4, 2018

The solution to this massive data challenge embedded the Aspire Content Processing Framework into the Cloudera Enterprise Data Hub as a Cloudera Parcel – a binary distribution format containing the program files, along with additional metadata used by Cloudera Manager.

Pharmaceutical 45

Pharmaceutical Unstructured Data Electronics Metadata 45

ProjectPro

NOVEMBER 15, 2021

Table of Contents 20 Open Source Big Data Projects To Contribute How to Contribute to Open Source Big Data Projects? 20 Open Source Big Data Projects To Contribute There are thousands of open-source projects in action today. This blog will walk through the most popular and fascinating open source big data projects.

Big Data 52

Big Data Project Metadata Programming Language 52

Netflix Tech

DECEMBER 14, 2018

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve.

Media 94

Media Database Metadata Data Schemas 94

ProjectPro

NOVEMBER 22, 2021

According to the Businesswire report , the worldwide big data as a service market is estimated to grow at a CAGR of 36.9% This clearly indicates that the need for Big Data Engineers and Specialists would surge in the future years. PySpark Interview Questions for Data Engineer Q1. from 2019 to 2026, reaching $61.42

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! But the concern is - how do you become a big data professional?

Big Data 52

Big Data Hadoop AWS Relational Database 52

Cloudera

AUGUST 21, 2020

More sources, data, and functionality were added to these platforms, expanding their value but adding to the complexity, such as: Streaming data ingestion. . Streaming data analytics. . Data science & engineering. Step 4: Cloudera Data Platform Option Recommendation & Trial/Set up. Let’s Talk!

Hadoop 73

Hadoop Big Data Cloud Kafka 73