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

AWS Big Data

AUGUST 21, 2023

We’ll compare searching for visual similarity (on the left) and textual similarity (on the right). Compare image and textual embeddings For example, sailboat shoes does a good job with both approaches, but white sailboat shoes does much better using visual similarity. In some cases, we get very similar results.

Data Processing 89

Data Processing Experimentation Visualization Metrics 89

Rocket-Powered Data Science

JULY 7, 2019

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). 5) Big Data Exploration. They cannot process language inputs generally.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

IBM Big Data Hub

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions.

Deep Learning 71

Deep Learning Experimentation Machine Learning Risk 71

FineReport

DECEMBER 19, 2019

At the same time, it also advocates visual exploratory analysis. The visualization component library of FineReport is very rich. It can be used as a portal for data reporting, or as a platform for business analysis. Generally, companies will store data in local databases or public clouds. Data Analysis Libraries.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Octopai

MAY 2, 2022

Today, your business users have the same perspective on data analytics. Your dashboards, charts, visualizations… they’re all products. . A successful data analytics team is one that can increase the quantity of data analytics products they develop in a given time while ensuring (and ideally, improving) the level of data quality.

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

AWS Big Data

JANUARY 9, 2024

Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. This functionality was initially released as experimental in OpenSearch Service version 2.4, and is now generally available with version 2.9.

Cost-Benefit 88

Cost-Benefit Visualization Modeling Machine Learning 88

Sisense

JULY 24, 2019

NLQ serves those users who are in a rush, or who lack the skills or permissions to model their data using visualization tools or code editors. So if we think about data access as a function of technical skills and the time it takes to get an answer, NLQ will be the first technology that users will turn to when looking for insights.

Analytics 89

Analytics Experimentation Metadata Big Data 89

O'Reilly on Data

SEPTEMBER 11, 2018

If we’re going to think about the ethics of data and how it’s used, then we have to take into account how data flows. Data, even “big data,” doesn’t stay in the same place: it wants to move. What might that responsibility mean?

Advertising 166

Advertising Insurance Experimentation Strategy 166

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. Example: A student is struggling with a complex math concept.

Cost-Benefit 95

Cost-Benefit Modeling Manufacturing Interactive 95

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Testing and Data Observability.

Testing 307

Testing Machine Learning Consulting Data Quality 307

AWS Big Data

OCTOBER 19, 2023

AWS Glue supports the Redshift MERGE SQL command within its data integration jobs. To learn more, refer to Exploring new ETL and ELT capabilities for Amazon Redshift from the AWS Glue Studio visual editor. If you need to handle delete operations in the source data lake, you will need to use a CDC-based approach. Choose ETL jobs.

Data Lake 109

Data Lake Data Warehouse Visualization Snapshot 109

IBM Big Data Hub

OCTOBER 20, 2023

Visual modeling: Combine visual data science with open source libraries and notebook-based interfaces on a unified data and AI studio. Automated development: With AutoAI , beginners can quickly get started and more advanced data scientists can accelerate experimentation in AI development.

Machine Learning 78

Machine Learning Manufacturing Cost-Benefit Deep Learning 78

Domino Data Lab

FEBRUARY 4, 2019

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. That body of work has much to offer the practice of leading data science teams. Taking a pulse.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Occam's Razor

AUGUST 12, 2013

There are few things more complicated in analytics (all analytics, big data and huge data!) Combine that with the excellent multi-channel conversion visualize (in the Overview section) and you have yourself a view of your marketing that will freak you out. You can visualize the impact of applying three models at one time.

Modeling 161

Modeling Optimization Marketing Interactive 161

Domino Data Lab

MAY 8, 2019

On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization. From my experiences leading data teams, when a business is facing difficult challenges, data visualizations can help or hurt.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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. You need to have these windows into the data and into your models and be able to test and change them visually.

Management 110

Management Machine Learning Experimentation Metrics 110

datapine

FEBRUARY 4, 2020

While your keyboard is burning and your fingers try to keep up with your brain and comprehend all the data you’re writing about, using an interactive online data visualization tool to set specific time parameters or goals you’ve been tracking can bring a lot of saved time and, consequently, a lot of saved money.

Reporting 280

Reporting Marketing Advertising Metrics 280

AWS Big Data

NOVEMBER 14, 2023

With a combination of low-latency data streaming and analytics, they are able to understand and personalize the user experience via a seamlessly integrated, self-reliant system for experimentation and automated feedback. Real-time streaming data technologies are essential for digital transformation.

IoT 55

IoT Data-driven Data Lake Data Strategy 55

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation. As you can see from the tiny confidence intervals on the graphs, big data ensured that measurements, even in the finest slices, were precise.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 105, -17) or even “Python” (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Occam's Razor

MAY 27, 2015

(even if you've never visited the site) has access to tons of intent signals from you right now, tons of third-party cookies that litter your browser right now, and immense Big Data and algorithms. It is being hyper-conservative when it comes to creativity and experimentation because of quant-issues. Does Yahoo!

Marketing Analytics 153

Marketing Analytics Marketing Analytics Advertising 153

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. . #9:

Data-driven 140

Data-driven Consulting Reporting Marketing 140