Cloudera

NOVEMBER 13, 2020

This is part of our series of blog posts on recent enhancements to Impala. We’ll discuss the architecture and features of Impala that enable low latencies on small queries and share some practical tips on how to understand the performance of your queries. Impala is architected to be the Speed-of-Thought query engine for your data.

Optimization 143

Optimization Metadata Statistics Cost-Benefit 143

datapine

SEPTEMBER 29, 2022

Engineered to be the “Swiss Army Knife” of data development, these processes prepare your organization to face the challenges of digital age data, wherever and whenever they appear. Through the 5 pillars that we just presented above, we also covered some techniques and tips that should be followed to ensure a successful process.

Data Quality 241

Data Quality Metrics Data-driven Management 241

datapine

NOVEMBER 15, 2022

4) Product Metrics Framework. As a PM, collecting information about your product performance, its features, the market adoption, etc., A common technique to break down the different types of key product metrics is using the AARRR framework , coined by venture capitalist Dave McClure. Table of Contents. is essential.

Metrics 141

Metrics KPI Measurement Dashboards 141

AWS Big Data

OCTOBER 14, 2024

Amazon EMR provides a big data environment for data processing, interactive analysis, and machine learning using open source frameworks such as Apache Spark, Apache Hive, and Presto. cd /home/ec2-user/SageMaker BASE_S3_PATH="s3://aws-blogs-artifacts-public/artifacts/BDB-4265" aws s3 cp "${BASE_S3_PATH}/0_create_tables_with_metadata.ipynb"./

Metadata 99

Metadata Data Lake Modeling Data Warehouse 99

AWS Big Data

MARCH 2, 2023

It adds tables to compute engines including Spark, Trino, PrestoDB, Flink, and Hive using a high-performance table format that works just like a SQL table. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. AWS Glue 3.0

Data Lake 135

Data Lake Data Processing Metadata Snapshot 135

Domino Data Lab

NOVEMBER 14, 2019

This Domino Data Science Field Note covers a proposed definition of interpretability and distilled overview of the PDR framework. Yet, despite the complexity (or because of it), data scientists and researchers curate and use different languages, tools, packages, techniques, and frameworks to tackle the problem they are trying to solve.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

Cloudera

FEBRUARY 25, 2021

AMPs enable data scientists to go from an idea to a fully working ML use case in a fraction of the time, with an end-to-end framework for building, deploying, and monitoring business-ready ML applications instantly. . The work of a machine learning model developer is highly complex. Built By Experts At The Leading Edge Of ML innovation.

Deep Learning 84

Deep Learning Machine Learning Visualization Forecasting 84

Smarten

MARCH 19, 2025

Generative Adversarial Network (GAN) This machine learning framework consists of two neural networks competing for a win or for the best result. Combining techniques can reduce costs, while delivering appropriate performance, efficiency and accuracy. It uses a large volume of data and parameters to train the model.

Cost-Benefit 52

Cost-Benefit Digital Transformation Manufacturing Machine Learning 52

Cloudera

SEPTEMBER 23, 2022

In a recent blog, Cloudera Chief Technology Officer Ram Venkatesh described the evolution of a data lakehouse, as well as the benefits of using an open data lakehouse, especially the open Cloudera Data Platform (CDP). Analytical engines can be scaled up (or down) on demand, as per the requirements of your workload.

Data Governance 109

Data Governance Strategy Enterprise Cost-Benefit 109

Juice Analytics

MARCH 11, 2021

Enabling users with features and capabilities to make them better in their job. Is the sales team in place to understand the product, the target audience and establish the sales framework for pushing the product? In a recent blog post , we described the differences between customer reporting and data products.

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

AWS Big Data

JUNE 10, 2024

This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used. A solution based on Apache Iceberg encompasses complete data management, featuring simple built-in table optimization capabilities within an existing storage solution.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

IBM Big Data Hub

JANUARY 24, 2024

Ethical hackers may also provide malware analysis, risk assessment, and other hacking tools and techniques to fix security weaknesses rather than cause harm. The red team simulates a real attackers’ tactics, techniques and procedures (TTPs) against the organization’s own system as a way to assess security risk.

Testing 72

Testing Risk Reporting IoT 72

AWS Big Data

JANUARY 17, 2024

By identifying these changes, the query engine can optimize the query to process only the relevant data, significantly reducing the processing time and resource requirements. Apache Hudi is an open source transactional data lake framework that greatly simplifies incremental data processing and the development of data pipelines.

Data Lake 114

Data Lake Snapshot Big Data Data-driven 114

AWS Big Data

SEPTEMBER 13, 2023

Use case overview AnyCompany Travel and Hospitality wanted to build a data processing framework to seamlessly ingest and process data coming from operational databases (used by reservation and booking systems) in a data lake before applying machine learning (ML) techniques to provide a personalized experience to its users.

Data Lake 110

Data Lake Data Processing Metadata Snapshot 110

Cloudera

AUGUST 25, 2020

With only about 35% of machine learning models making into production in the enterprise ( IDC ), it’s no wonder that production machine learning has become one of the most important focus areas for data scientists and ML engineers alike. They can take many forms from Python-based rest APIs to R scripts to distributed frameworks like SparkML.

Machine Learning 78

Machine Learning Metrics Modeling Data Science 78

IBM Big Data Hub

MARCH 27, 2024

The US Environmentally-Extended Input-Output (USEEIO) is a lifecycle assessment (LCA) framework that traces economic and environmental flows of goods and services within the United States. This framework helps streamline and simplify the process for businesses to calculate Scope 3 emissions.

Experimentation 73

Experimentation Deep Learning Modeling Data-driven 73

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . Given this context, how can financial institutions reap the benefits of modern machine learning approaches, while still being compliant to their MRM framework?

Risk 64

Risk Modeling Machine Learning Data Quality 64

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

It also owns Google’s internal time series forecasting platform described in an earlier blog post. But even here, a greater concern is the time invested by data scientists (mostly at the development stage) in data analysis and cleaning, feature engineering, and model development. Our team does a lot of forecasting.

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

Cloudera

AUGUST 25, 2020

Machine Learning and AI provide powerful predictive engines that rely on historical data to fit the models. I am optimistic that what we’ll see over the next 5 years is a mass acceleration and adoption of simulation techniques that complement the continuing innovation in the Machine Learning space. .

Prescriptive Analytics 74

Prescriptive Analytics Technology Machine Learning Risk 74

IBM Big Data Hub

MAY 13, 2024

This blog series demystifies enterprise generative AI (gen AI) for business and technology leaders. It provides simple frameworks and guiding principles for your transformative artificial intelligence (AI) journey. In the previous blog , we discussed the differentiated approach by IBM to delivering enterprise-grade models.

Modeling 70

Modeling Cost-Benefit Risk Testing 70

datapine

JULY 24, 2019

They can have a lot of different features, mainly being a customizable interface, a certain level of interactivity as well as the possibility to pull data in real-time from multiple sources. Analytical: This type of dashboard is engineered to provide detailed data analyses pertaining to data trends (the what, the why, the how).

Dashboards 148

Dashboards Business Intelligence Visualization KPI 148

IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI uses advanced machine learning algorithms and techniques to analyze patterns and build statistical models. The quality of outputs depends heavily on training data, adjusting the model’s parameters and prompt engineering, so responsible data sourcing and bias mitigation are crucial. Garbage in, garbage out.

Enterprise 118

Enterprise Testing Modeling Data-driven 118

Occam's Razor

AUGUST 13, 2012

Yehoshua I've covered this topic in detail in this blog post: Multi-Channel Attribution: Definitions, Models and a Reality Check. Attribution modeling is a feature available only in Google Analytics Premium, a paid version. A Framework For Critical Thinking.

Modeling 125

Modeling Metrics Data Quality Data-driven 125

Cloudera

OCTOBER 17, 2017

In this blog, we provide a few examples that show how organizations put deep learning to work. Deep learning is a proven technique and a key driver for digital transformation. Users can download and experiment with the latest libraries and frameworks in customizable settings, and easily share projects with peers. Deeplearning4j.

Deep Learning 47

Deep Learning Data Science Machine Learning Modeling 47

Laminar Security

SEPTEMBER 18, 2023

I’ve previously discussed the risk of shadow data (those data stores you didn’t even know you had), and the team specifically dove into how versioning (a feature used to protect from accidental deletion) can unintentionally create shadow data. In this case, the engineer may want to create a data dump to use for testing.

Risk 128

Risk Testing Data Governance Metadata 128

The Unofficial Google Data Science Blog

APRIL 17, 2017

In this post, we recount how we approached the task, describing initial stakeholder needs, the business and engineering contexts in which the challenge arose, and theoretical and pragmatic choices we made to implement our solution. The demand for time series forecasting at Google grew rapidly along with the company over its first decade.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Cloudera

MAY 28, 2019

Gartner states that “By 2022, 75% of new end-user solutions leveraging machine learning (ML) and AI techniques will be built with commercial instead of open source platforms” ¹. Learn more about the Cloudera Data Science Workbench for the end-to-end ML workflow at our bi-weekly webinar series featuring live expert demos and Q&A.

Data Science 50

Data Science Machine Learning Data Strategy Cost-Benefit 50

Cloudera

OCTOBER 25, 2022

The cloud data lakehouse brings multiple processing engines (SQL, Spark, and others) and modern analytical tools (ML, data engineering, and business intelligence) together in a unified analytical environment. Consider this practice the most important function and foundation of your cloud security framework.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

Alation

FEBRUARY 20, 2020

By interacting with Tableau’s features to re-label data columns and build derived metrics, Tableau users were effectively documenting and modeling data on their own, often without realizing it. As teams work with Kylo, it captures the basic, technical metadata in the core source foundational framework.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

Andrew White

JANUARY 9, 2022

– In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. Can you remind where we can find the mentioned blog? So much hype compares electric vehicles to traditional engines. Can you provide a link to your blog, or will we get notice of your info posted through email?

Analytics 64

Analytics Measurement Data-driven Modeling 64

Domino Data Lab

JULY 28, 2021

Data scientists, analysts and ML engineers may move from one project to another, or they may leave the organization while new team members are brought on board. The Develop stage is where data scientists build and assess models based on a variety of different modeling techniques. Develop Stage. Deploy Stage. MLOps in the DSLC.

Data Science 59

Data Science Enterprise Modeling Experimentation 59

Alation

APRIL 14, 2022

Once migration is complete, it’s important that your data scientists and engineers have the tools to search, assemble, and manipulate data sources through the following techniques and tools. A technique to automate changes in iterative passes. A technique to automate changes in iterative passes. Parametrization.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

Ontotext

NOVEMBER 23, 2023

The RDF4J framework, and, by extension, GraphDB, offers a smart approach to this. At the lowest level, to the engine, there’s no difference between “data” and “SHACL shapes” — it’s all triples. Most data engineers are not Java developers. And besides Smaug, we have 1,000 other dragons.

Data Quality 69

Data Quality Reporting Metadata Big Data 69

IBM Big Data Hub

MAY 26, 2023

Overall foundational pillars of the AWS security framework include the following: Compliance: AWS provides a range of compliance certifications and attestations that are relevant to the life sciences industry, including HIPAA, HITRUST and GxP. Data protection and privacy: Each AWS customer maintains ownership of their own data.

Consulting 73

Consulting Cost-Benefit Machine Learning Optimization 73

Cloudera

SEPTEMBER 23, 2022

In a recent blog, Cloudera Chief Technology Officer Ram Venkatesh described the evolution of a data lakehouse, as well as the benefits of using an open data lakehouse, especially the open Cloudera Data Platform (CDP). Analytical engines can be scaled up (or down) on demand, as per the requirements of your workload.

Cost-Benefit 52

Cost-Benefit Software Data-driven Data Warehouse 52

Domino Data Lab

MARCH 6, 2019

This blog recaps Miner & Kasch ’s first Maryland Data Science Conference hosted at UMBC and dives into the Deep Learning on Imagery and Text talk presented by Florian Muellerklein and Bryan Wilkinson. Introduction. The conference was not without hiccups. You can see a complete list of talks see here. Deep Learning on Imagery and Text.

Deep Learning 55

Deep Learning Data Science Machine Learning Data Processing 55

Sisense

MARCH 18, 2020

They should do this by integrating mitigation techniques and policies, such as monitoring, patching, and vulnerability reporting. This danger looms greater than ever today thanks to machine learning techniques that are fundamentally changing the way software is made. Developing a better world.

Software 52

Software Machine Learning Internet of Things Risk 52