FineReport

DECEMBER 11, 2019

In the past few years, the term “data science” has been widely used, and people seem to see it in every field. Big Data”, “Business Intelligence”, “ Data Analysis ” and “ Artificial Intelligence ” came into being. For a while, everyone seems to have begun to learn data analysis. Big data is changing our world.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

Octopai

MAY 2, 2022

Common elements of DataOps strategies include: Collaboration between data managers, developers and consumers A development environment conducive to experimentation Rapid deployment and iteration Automated testing Very low error rates. But the approaches and principles that form the basis of DataOps have been around for decades.

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

CIO Business Intelligence

MAY 16, 2023

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data.

Advertising 105

Advertising Recreation/Entertainment Experimentation Enterprise 105

AWS Big Data

MAY 2, 2023

After the data has been retrieved, it’s stored in the S3 bucket. Test the feature To test this feature, run the producer DAG. Removal of experimental Smart Sensors. Test the feature Upload the four sample text files from the local data folder to an S3 bucket data folder. Apache Airflow v2.4.3

Testing 98

Testing Experimentation Management Metadata 98

IBM Big Data Hub

DECEMBER 14, 2023

The extension of the CIO office’s dedicated data center to the IBM public cloud allowed for experimentation and growth with zero risk. The Terraform automation and automated regression testing allowed me to reliably change the connection mechanism from direct link to VPN. Automated regression tests are a dynamite.

Experimentation 73

Experimentation Testing Software Management 73

AWS Big Data

AUGUST 21, 2023

In particular, our experimentation shows that hybrid search, combining lexical and vector approaches, typically results in a 15% improvement in search result quality over lexical or vector search alone on industry-standard test sets, as measured by the NDCG@10 metric (Normalized Discounted Cumulative Gain in the first 10 results).

Data Processing 89

Data Processing Experimentation Visualization Metrics 89

The Unofficial Google Data Science Blog

JANUARY 14, 2016

by AMIR NAJMI Running live experiments on large-scale online services (LSOS) is an important aspect of data science. We must therefore maintain statistical rigor in quantifying experimental uncertainty. In this post we explore how and why we can be “ data-rich but information-poor ”. And an LSOS is awash in data, right?

Experimentation 41

Experimentation Statistics Metrics Measurement 41

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. The AGI analyzes the data and identifies a rare genetic mutation linked to a specific disease.

Cost-Benefit 96

Cost-Benefit Modeling Manufacturing Interactive 96

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

AWS Big Data

JANUARY 9, 2024

This functionality was initially released as experimental in OpenSearch Service version 2.4, We encourage search practitioners to begin testing the search methods available in order to find the right fit for your use case. and is now generally available with version 2.9.

Cost-Benefit 89

Cost-Benefit Visualization Modeling Machine Learning 89

DataKitchen

APRIL 13, 2021

Testing and Data Observability. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Genie — Distributed big data orchestration service by Netflix.

Testing 307

Testing Machine Learning Consulting Data Quality 307

The Unofficial Google Data Science Blog

JULY 22, 2020

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Cloudera

AUGUST 2, 2018

Simply put, modern data warehousing enables our customers to confidently share petabytes of verified data across thousands of users while surpassing demands of SLAs and limited budgets. Where traditional data warehousing begins to fall apart – we step in with Cloudera Data Warehouse.

Data Warehouse 53

Data Warehouse Insurance Experimentation Software 53

bridgei2i

APRIL 28, 2020

A three-time recipient of Gartner’s Annual Thought Leadership award, he’s the originator of the field of Infonomics, which is about evaluating and accounting for data or information as an asset. He’s also the man who coined 3Vs- volume, velocity, and variety now commonly used in defining big data.

Enterprise 103

Enterprise Data Analytics Analytics Forecasting 103

AWS Big Data

JULY 3, 2023

Look – ahead bias – This is a common challenge in backtesting, which occurs when future information is inadvertently included in historical data used to test a trading strategy, leading to overly optimistic results. To comply with licensing considerations, we cannot provide a sample of the ETF constituents data.

Snapshot 80

Snapshot Data Lake Testing Strategy 80

Rocket-Powered Data Science

OCTOBER 16, 2020

Be sure to listen to the full recording of our lively conversation, which covered Data Literacy, Data Strategy, Data Leadership, and more. The data age has been marked by numerous “hype cycles.” We build models to test our understanding, but these models are not “one and done.” The Age of Hype Cycles.

Digital Transformation 142

Digital Transformation Experimentation Data Strategy Strategy 142

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

The Unofficial Google Data Science Blog

JULY 31, 2016

At the end of the semester, you administer a proficiency test to the students and compare test performance across the groups. For example, you might compare the average test score among students exposed to the new curriculum to the average score among the controls. Sounds straightforward, right?

Experimentation 42

Experimentation Testing Measurement Metrics 42

AWS Big Data

JULY 26, 2023

From preview to GA and beyond Today, we are excited to announce the preview of the vector engine, making it available for you to begin testing it out immediately. We recognize that many of you are in the experimentation phase and would like a more economical option for dev-test.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

Occam's Razor

AUGUST 12, 2013

There are few things more complicated in analytics (all analytics, big data and huge data!) You only have to think about it for five seconds to realize it passes the ultimate test for everything: Common sense. Test that hypothesis using a percent of your budget and measure results. Or we could not.)

Modeling 161

Modeling Optimization Marketing Interactive 161

AWS Big Data

MAY 24, 2023

Some of the important non-functional use cases for an S3 data lake that organizations are focusing on include storage cost optimizations, capabilities for disaster recovery and business continuity, cross-account and multi-Region access to the data lake, and handling increased Amazon S3 request rates. write.tags.write-tag-name and s3.delete.tags.delete-tag-name

Data Lake 80

Data Lake Snapshot Metadata Optimization 80

Cloudera

JUNE 6, 2019

When a mix of batch, interactive, and data serving workloads are added to the mix, the problem becomes nearly intractable. We sometimes refer to this as splitting “dev/test” from “production” workloads, but we can generalize the approach by referring to the overall priority of the workload for the business.

Metadata 87

Metadata Data Lake Optimization Strategy 87

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

One purpose of data science is to inform actual “business decisions”, or, more precisely, decisions of importance to the team or community served by the data scientist. The beliefs of this community are always evolving, and the process of thoughtfully generating, testing, refuting and accepting ideas looks a lot like Science.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

Domino Data Lab

MAY 8, 2019

They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Keep in mind that data science is fundamentally interdisciplinary. Here’s where I get baffled by people who use words such as agile or lean to describe process for data science.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

datapine

FEBRUARY 4, 2020

Although keep in mind your long-term performance is one of the most important parameters to decide in which way you have to adjust your campaigns and efforts, weekly summaries can decrease the number of interdepartmental meetings between marketing professionals, and provide a faster way to analyze big data. click to enlarge**.

Reporting 280

Reporting Marketing Advertising Metrics 280

Occam's Razor

SEPTEMBER 15, 2014

Media-Mix Modeling/Experimentation. Upsight (nee Kontagent) provides mobile app analytics, with a pinch of advanced segmentation (including sweet cohort analysis ) and big data mining thrown in for good measure. Media-Mix Modeling/Experimentation. Dive into Mobile Reporting and Analysis. Implement Cross-Device Tracking.

Metrics 141

Metrics Reporting Analytics Marketing 141

Occam's Razor

AUGUST 13, 2012

If you want to make the smartest decisions about your budget allocation then leveraging the time tested methodology of media mix modeling (at its core powered by controlled experiments) is the only way to go. See point #4 here: A Big Data Imperative: Driving Big Action. Did I not say we got some incredible questions?

Modeling 124

Modeling Metrics Data Quality Data-driven 124

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. There is no longer always intentionality behind the act of data collection — data are not collected in response to a hypothesis about the world, but for the same reason George Mallory climbed Everest: because it’s there. We ought not dredge our data.

Experimentation 61

Experimentation Testing Statistics Metrics 61

Occam's Razor

JANUARY 7, 2014

First… it is important to realize that big data's big imperative is driving big action. Second… well there is no second, it is all about the big action and getting a big impact on your bottom-line from your big investment in analytics processes, consulting, people and tools.

Data-driven 140

Data-driven Consulting Reporting Marketing 140

IBM Big Data Hub

SEPTEMBER 25, 2023

There may be inaccuracy because of sampling, but it allows users to discover new viewpoints within the data. If the exploratory work needs to move on to testing and production, they can plan appropriately. Data Exploration and Innovation: The flexibility of Presto has encouraged data exploration and experimentation at Uber.

OLAP 93

OLAP Data Lake Data-driven Snapshot 93

Occam's Razor

APRIL 29, 2013

It turns out that Marketers, especially Digital Marketers, make really silly mistakes when it comes to data. Small data. Here's why… Real-time data is very expensive. It is expensive from a systems/platforms/data processing/data reporting perspective. Actually you don't even have to have a click!!

Marketing 166

Marketing Metrics Advertising Measurement 166

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Years and years of practice with R or "Big Data." Test for analytics experience AND explore the level of analytical thinking the job candidate possesses.

Marketing 136

Marketing Analytics Machine Learning Strategy 136