Ascend.io

JUNE 8, 2023

Treating data as a product is more than a concept; it’s a paradigm shift that can significantly elevate the value that business intelligence and data-centric decision-making have on the business. Data Pipelines Data pipelines are the indispensable backbone for the creation and operation of every data product.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Monte Carlo

JANUARY 23, 2024

Gen AI can whip up serviceable code in moments — making it much faster to build and test data pipelines. It can show me how it built that chart, which dataset it used, and show me the metadata.” Embedding conversational AI capabilities into business intelligence products is an example of a good starting point.

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

Maxime Beauchemin

JANUARY 20, 2017

I joined Facebook in 2011 as a business intelligence engineer. Instead, Facebook came to realize that the work we were doing transcended classic business intelligence. Data is simply too centric to the company’s activity to have limitation around what roles can manage its flow.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Databand.ai

DECEMBER 29, 2022

Mico’s ability to help companies gain ROI from their business intelligence investments has been sought out by Fortune 500 companies. Vin is also a course instructor at HROI Certification Training, teaching courses in data and AI technical strategy, value-centric data, and transitioning from a tactical to strategic mindset.

BI 52

BI Consulting Data Science Data Governance 52

Airbnb Tech

JUNE 1, 2021

Furthermore, pipelines built downstream of core_data created a proliferation of duplicative and diverging metrics. When a metric is defined in Minerva, authors are required to provide important self-describing metadata. The tool clearly shows the step-by-step computation the Minerva pipeline will follow to generate the output.

Datasets 52

Datasets Pipeline-centric Metadata Data Science 52

phData: Data Engineering

JULY 18, 2023

This typically results in long-running ETL pipelines that cause decisions to be made on stale or old data. Business-Focused Operation Model: Teams can shed countless hours of managing long-running and complex ETL pipelines that do not scale. This enables an automated continuous integration/continuous deployment system (CI/CD).

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

AltexSoft

JULY 18, 2023

With its native support for in-memory distributed processing and fault tolerance, Spark empowers users to build complex, multi-stage data pipelines with relative ease and efficiency. More files within a workload mean more metadata to parse and more tasks to schedule, which can significantly slow down processing.

Big Data 52

Big Data Data Process Process Hadoop 52