DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

MAY 4, 2023

Welcome to the era of data. The sheer volume of data captured daily continues to grow, calling for platforms and solutions to evolve. The Amazon Sustainability Data Initiative (ASDI) uses the capabilities of Amazon S3 to provide a no-cost solution for you to store and share climate science workloads across the globe.

Data Processing 97

Data Processing Metadata Informatics Interactive 97

Domino Data Lab

MAY 1, 2019

This Domino Data Science Field Note provides highlights and excerpted slides from Chloe Mawer ’s “ The Ingredients of a Reproducible Machine Learning Model ” talk at a recent WiMLDS meetup. Mawer is a Principal Data Scientist at Lineage Logistics as well as an Adjunct Lecturer at Northwestern University.

Machine Learning 81

Machine Learning Testing Data Science Modeling 81

O'Reilly on Data

MARCH 7, 2019

Language understanding benefits from every part of the fast-improving ABC of software: AI (freely available deep learning libraries like PyText and language models like BERT ), big data (Hadoop, Spark, and Spark NLP ), and cloud (GPU's on demand and NLP-as-a-service from all the major cloud providers).

Deep Learning 227

Deep Learning Testing Machine Learning Modeling 227

IBM Big Data Hub

AUGUST 28, 2023

With nearly 5 billion users worldwide—more than 60% of the global population —social media platforms have become a vast source of data that businesses can leverage for improved customer satisfaction, better marketing strategies and faster overall business growth. What is text mining? How does text mining work?

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

CIO Business Intelligence

MARCH 24, 2023

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Peter James Thomas

AUGUST 18, 2018

No this article has not escaped from my Maths & Science section , it is actually about data matters. But first of all, channeling Jennifer Aniston [1] , “here comes the Science bit – concentrate” Shared Shapes. That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

CIO Business Intelligence

AUGUST 1, 2023

Data collection on tribal languages has been undertaken for decades, but in 2012, those working at the Myaamia Center and the National Breath of Life Archival Institute for Indigenous Languages realized that technology had advanced in a way that could better move the process along.

Risk 98

Risk IT Software Digital Transformation 98

O'Reilly on Data

MARCH 23, 2021

There is a growing disbelief and distrust in basic science and government. A consensual hallucination experienced daily by billions of legitimate operators, in every nation, by children being taught mathematical concepts… A graphic representation of data abstracted from the banks of every computer in the human system.

Internet Publishing and Broadcasting 317

Internet Publishing and Broadcasting Broadcasting Data-driven Interactive 317

Alation

FEBRUARY 13, 2020

This article is based on a podcast Ron Powell conducted with Sharon Graves, Enterprise Data and BI Tools Evangelist for GoDaddy, about data curation, data stewardship, and data catalogs. His focus is on business intelligence, analytics, big data, and data warehousing. What did that involve?

Digital Transformation 52

Digital Transformation Data-driven Business Intelligence Big Data 52

O'Reilly on Data

AUGUST 4, 2022

In the 1950s, machine translation of Russian into English was considered to be no more complex than dictionary lookups and templated phrases. The claim is that AGI is now simply a matter of improving performance, both in hardware and software, and making models bigger, using more data and more kinds of data across more modes.

Machine Learning 262

Machine Learning Modeling Statistics Software 262

Insight

JULY 23, 2019

I frequently run into this issue in my data science workflow with complex objects in libraries, like TensorFlow. kwonlydefaults is a dictionary with keyword-only arg default values. annotations is a dictionary specifying any type annotations. args contains the argument names. kwonlyargs lists names of keyword-only args.

Testing 55

Testing Data Science IT Interactive 55

Cloudera

NOVEMBER 3, 2021

Have you ever asked a data scientist if they wanted their code to run faster? Today, deep learning and GPUs are practically synonymous. While deep learning is an excellent use of the processing power of a graphics card, it is not the only use. You would probably get a more varied response asking if the earth is flat.

Deep Learning 115

Deep Learning Machine Learning Data Science Cost-Benefit 115

O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

Octopai

DECEMBER 12, 2021

A data asset is only an asset if you can use it to help your organization. What enables you to use all those gigabytes and terabytes of data you’ve collected? Metadata is the pertinent, practical details about data assets: what they are, what to use them for, what to use them with. Where does metadata come from?

Metadata 93

Metadata Management Data Quality Data Governance 93

Peter James Thomas

SEPTEMBER 17, 2018

More recently, I have started writing some entirely Maths or Science-focused articles, starting with my book about Group Theory and Particle Physics, Glimpses of Symmetry [2]. For this reason, I will periodically share selected articles from the Maths & Science Section here on the main site. Follow @peterjthomas.

Machine Learning 40

Machine Learning Data Science Analytics IT 40

Sisense

MAY 26, 2020

In Talking Data , we delve into the rapidly evolving worlds of Natural Language Processing and Generation. Text data is proliferating at a staggering rate, and only advanced coding languages like Python and R will be able to pull insights out of these datasets at scale. Today, text data is everywhere. Semantic meaning of words.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. The Importance of Exploratory Analytics in the Data Science Lifecycle. Exploratory analysis is a critical component of the data science lifecycle. For one, Python remains the leading language for data science research. ref: [link].

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106

Domino Data Lab

JULY 1, 2021

The model achieves relatively high accuracy and all data and code is freely available in the article. statistical model-based techniques – Using Machine Learning we can streamline and simplify the process of building NER models, because this approach does not need a predefined exhaustive set of naming rules.

Modeling 111

Modeling Statistics Testing Metrics 111

Domino Data Lab

APRIL 6, 2021

Training machine learning models, especially neural networks, is compute-intensive. Then I’ll briefly mention several higher-level toolkits for machine learning that leverage Ray. Let’s use an actor to hold the DNS data. While it emerged in the ML/AI world, it is not restricted to data science applications at all.

Data Science 81

Data Science Optimization Machine Learning Modeling 81

Peter James Thomas

MAY 3, 2019

As part of my consulting business , I end up thinking about Data Capability Frameworks quite a bit. Sometimes this is when I am assessing current Data Capabilities, sometimes it is when I am thinking about how to transition to future Data Capabilities. Collation of Data to provide Information.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

Domino Data Lab

OCTOBER 9, 2019

Paco Nathan’s latest article covers data practices from the National Oceanic and Atmospheric Administration (NOAA) Environment Data Management (EDM) workshop as well as updates from the AI Conference. Data Science meets Climate Science. Data veracity, data stewardship, and heros of data science.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

Domino Data Lab

AUGUST 26, 2019

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. Data scientists, machine learning (ML) researchers, and business stakeholders have a high-stakes investment in the predictive accuracy of models. Introduction.

Testing 79

Testing Modeling Machine Learning Metrics 79

Domino Data Lab

AUGUST 20, 2019

Many thanks to AWP Pearson for the permission to excerpt “Manual Feature Engineering: Manipulating Data for Fun and Profit” from the book, Machine Learning with Python for Everyone by Mark E. Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models.

Testing 68

Testing Modeling Interactive Measurement 68

Smarten

APRIL 24, 2019

The Merriam-Webster dictionary defines the word ‘augment’ this way: ‘to make greater, more numerous, larger or more intense’ If you are wondering how this applies to the term ‘augmented analytics’, you are not alone. It automates data preparation and allows for easy data sharing.

Business Intelligence 0

Business Intelligence Analytics IT Metrics 0

Domino Data Lab

AUGUST 22, 2019

While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry. Utilizing NLP helps researchers and data scientists complete core tasks faster. Example 11.4

Deep Learning 111

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AWS Big Data

JULY 18, 2023

Different user personas such as developers, data scientists, system operators, or architects in your organization may need access to the Apache Airflow UI. It then forwards the login request to the Amazon MWAA authenticator AWS Lambda function with the JWT token included in the request header in the x-amzn-oidc-data parameter.

Data Processing 75

Data Processing Management Software Machine Learning 75

Peter James Thomas

AUGUST 30, 2018

Based on Kaggle’s State of Data Science Survey 2017 (Sample size: 10,153). The text in the above exhibit is not that clear [2] , so here are the 20 top challenges [3] faced by those running Data Science teams in human-readable form: #. Dirty Data. Lack of Data Science talent in the organization.

Data Science 75

Data Science Data Quality Machine Learning Business Intelligence 75

Alation

DECEMBER 15, 2021

Modern business is built on a foundation of trusted data. Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

AWS Big Data

JUNE 14, 2023

The AWS Professional Services (ProServe) Insights team builds global operational data products that serve over 8,000 users within Amazon. In this post, we discuss how QuickSight has helped us improve our performance, democratize our data, and provide insights to our internal customers at scale.

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Dashboards KPI Scorecard Consulting 77