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

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

Data Engineering Weekly

OCTOBER 30, 2022

We saw in the Data Catalog poll how far it has to go to be helpful and active within a data workflow. The author narrates the data contract, why it is the foundation for building data mesh, and how it glue data catalogs, glossary and data quality systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 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

Data Engineering Weekly

MAY 16, 2023

In the second part, we will focus on architectural patterns to implement data quality from a data contract perspective. Why is Data Quality Expensive? I won’t bore you with the importance of data quality in the blog. In the 'Write' stage, we capture the computed data in a log or a staging area.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

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

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

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 16, 2022

Weak model lineage can result in reduced model performance, a lack of confidence in model predictions and potentially violation of company, industry or legal regulations on how data is used. . Within the CML data service, model lineage is managed and tracked at a project level by the SDX. Figure 02: ML Model Lineage with SDX.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

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

Cloudera

SEPTEMBER 28, 2020

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Data Science and machine learning workloads using CDSW.

Cloud 131

Cloud Kafka Professional Services Metadata 131

Maxime Beauchemin

JANUARY 20, 2017

They’re highly analytical, and are interested in data visualization. Unlike data scientists — and inspired by our more mature parent, software engineering  — data engineers build tools, infrastructure, frameworks, and services. Sure, there’s a need to abstract the complexity of data processing, computation and storage.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Snowflake

MAY 22, 2023

Cross-Cloud Snowgrid Account Replication expands replication beyond databases – general availability Account Replication, now generally available, expands replication beyond databases to account metadata and integrations, making business continuity truly turnkey. Read our announcement blog post for more.

Healthcare 52

Healthcare Scala Medical Transportation 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value. ML workflow, ubr.to/3EJHjvm

Engineering 82

Engineering Raw Data Data Science Scala 82

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

ProjectPro

AUGUST 24, 2021

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. And, out of these professions, this blog will discuss the data engineering job role.

Data Engineering 52

Data Engineering Data Engineer Coding Project 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 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

ProjectPro

NOVEMBER 22, 2021

StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. To define the columns, PySpark offers the pyspark.sql.types import StructField class, which has the column name (String), column type (DataType), nullable column (Boolean), and metadata (MetaData).

Hadoop 52

Hadoop Python Datasets Metadata 52

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

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 on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects. Data Ingestion.

Machine Learning 136

Machine Learning Datasets Data Science Raw Data 136

ProjectPro

OCTOBER 20, 2021

If you are unsure, be vocal about your thought process and the way you are thinking – take inspiration from the examples below and explain the answer to the interviewer through your learnings and experiences from data science and machine learning projects. Alright, we have had enough fun building up to this moment.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

Cloudera

DECEMBER 20, 2021

In the past year, the Bank of the West has begun using the Cloudera platform to establish a data governance and security framework to manage and protect its customers’ sensitive information. The platform is centralizing the data, data management & governance, and building custom controls for data ingestion into the system.

Government 86

Government Data Security Banking Metadata 86

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

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 84

Data Lake Business Intelligence Metadata Data Warehouse 84

DataKitchen

SEPTEMBER 21, 2023

In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers. For companies where data is a critical asset, this erosion of trust can have long-term business implications, compromising decision-making and strategic initiatives.

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

Cloudera

APRIL 22, 2021

Cloudera has partnered with Cisco in helping build the Cisco Validated design (CVD) for Apache Ozone. This CVD is built using Cloudera Data Platform Private Cloud Base 7.1.5 Collects and aggregates metadata from components and present cluster state. Metadata in cluster is disjoint across components.

Pipeline-centric 98

Pipeline-centric Data Lake Hadoop Metadata 98

Cloudera

AUGUST 21, 2020

Will building on open-source remain our safest option? . How do we maintain visibility to all data and systems for security/compliance? They took major investments to develop, build, tune, and stabilize to a productive state by the early developers of these technologies. Streaming data analytics. . From start to finish.

Hadoop 73

Hadoop Big Data Cloud Kafka 73

Cloudera

SEPTEMBER 6, 2018

Given what we know about current anti-money laundering systems, if we wanted to build one from scratch today, we might come up with the following requirements. The system must: Ingest, process, analyze, store, and serve all types of AML data, be it structured (database tables), unstructured (contracts, e-mails, etc.),

Banking 40

Banking Machine Learning Big Data Scala 40

Cloudera

JUNE 16, 2022

The ability to perform analytics on data as it is created and collected (a.k.a. real-time data streams) and generate immediate insights for faster decision making provides a competitive edge for organizations. . CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report.

Kafka 84

Kafka Manufacturing Data Lake SQL 84

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 90

Data Engineering Data Engineer Cloud Engineering 90

phData: Data Engineering

JULY 18, 2023

Why Migrate to a Modern Data Stack? With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. The combination of these technologies has become collectively known as the Modern Data Stack.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 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. Take Ops to Zero.

Cloud Computing 114

Cloud Computing Cloud Storage Data Science Government 114