AWS Big Data

APRIL 3, 2024

We discuss how to visualize data quality scores in Amazon DataZone, enable AWS Glue Data Quality when creating a new Amazon DataZone data source, and enable data quality for an existing data asset. If the asset has AWS Glue Data Quality enabled, you can now quickly visualize the data quality score directly in the catalog search pane.

Data Quality 91

Data Quality Visualization Metadata Metrics 91

datapine

MAY 14, 2019

We gave you a curated list of our top 15 data analytics books , top 18 data visualization books , top 16 SQL books – and, as promised, we’re going to tell you all about the world’s best books on data science. 8) “Storytelling With Data: A Data Visualization Guide for Business Professionals” by Cole Nussbaumer Knaflic.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

datapine

SEPTEMBER 27, 2022

We have already given you our top data visualization books , top business intelligence books , and best data analytics books. This piece, published in 2012, offers a step-to-step guide on everything related to SQL. Its visually rich format is designed for the way your brain works, not in a text-heavy approach that puts you to sleep.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. Figure 4: Visualization of a central composite design. Journal of Statistical Software, 56(1):1-56, 2014. [5] Hedayat, N.J.A.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Depict Data Studio

NOVEMBER 4, 2022

I published my first video on November 4, 2012…. ” I’d been a formal statistics tutor and Spanish tutor in college through a small invite-only program. I especially love this lesson on using colored phrases for qualitative data visualization, which I made for Jon Schwabish’s channel. and the rest was history!

Dashboards 75

Dashboards Testing Software Consulting 75

Domino Data Lab

AUGUST 8, 2019

He’s been out of Wolfram for a while and writing exquisite science books including Elements: A Visual Explanation of Every Known Atom in the Universe and Molecules: The Architecture of Everything. They tend to use less machine learning, but more advanced statistical practices, since the outcomes (government policies, etc.)

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Domino Data Lab

SEPTEMBER 25, 2019

A big part of statistics, particularly for financial and econometric data, is analyzing time series, data that are autocorrelated over time. predict(usBest, n.ahead=5, se.fit=TRUE) $pred Time Series: Start = 2012 End = 2016 Frequency = 1 [1] 49292.41 Chapter Introduction: Time Series and Autocorrelation. > attGarch.

Forecasting 87

Forecasting Modeling Statistics Optimization 87

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. They may contain parameters in the statistical sense, but often they simply contain strategically placed 0's and 1's indicating which bits of $alpha_t$ are relevant for a particular computation. by STEVEN L.

Forecasting 64

Forecasting Statistics Modeling Software 64

The Unofficial Google Data Science Blog

MARCH 31, 2016

We often use statistical models to summarize the variation in our data, and random effects models are well suited for this — they are a form of ANOVA after all. Often our data can be stored or visualized as a table like the one shown below. Cambridge University Press, (2012). [4] 4] Bradley Efron, and Carl Morris. 7] Nicholas A.

Modeling 40

Modeling Statistics Advertising Testing 40

Domino Data Lab

MARCH 3, 2019

While image data has been the stalwart for deep learning use cases since the proverbial “ AlexNet moment ” in 2011-2012, and a renaissance in NLP over the past 2-3 years has accelerated emphasis on text use cases, we note that structured data is at the top of the list in enterprise. Spark, Kafka, TensorFlow, Snowflake, etc.,

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

CIO Business Intelligence

JULY 2, 2022

For example, IDC data shows that 2021 there was a boom in monitor sales, with the highest volume of monitors shipped since 2012, at 143.6 million , and this figure is likely due to many professionals giving their home offices a refresh.

Statistics 95

Statistics Sales Visualization Technology 95

CIO Business Intelligence

JULY 5, 2022

For example, IDC data shows that 2021 there was a boom in monitor sales, with the highest volume of monitors shipped since 2012, at 143.6 million , and this figure is likely due to many professionals giving their home offices a refresh.

Statistics 89

Statistics Sales Visualization Technology 89

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. You started to see point solutions.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

IBM Big Data Hub

OCTOBER 12, 2023

However, AI capabilities have been evolving steadily since the breakthrough development of artificial neural networks in 2012, which allow machines to engage in reinforcement learning and simulate how the human brain processes information. Human intervention was required to expand Siri’s knowledge base and functionality.

Machine Learning 70

Machine Learning Deep Learning Interactive Modeling 70

datapine

DECEMBER 28, 2021

1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?

Statistics 363

Statistics Advertising Visualization Data mining 363

Sisense

DECEMBER 11, 2019

And he explained that the leap to visual-based data discovery put analytics in the hands of data experts working in different lines of business, rather than in IT, where bottlenecks could previously occur, and reporting could take much longer. From a startup in 2012, it is now valued at $3.2 A true unicorn.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

CIO Business Intelligence

FEBRUARY 3, 2023

Much of the work is accomplished by dragging and dropping components in a visual designer, but developers can also adjust the system-generated code in an IDE. Power Advisor tracks statistics about performance to locate bottlenecks and other issues. It offers migration from desktop to a cloud solution, and an open-source edition.

Data-driven 145

Data-driven Interactive Enterprise Statistics 145

datapine

MAY 17, 2021

Data discovery is a term used to describe the process for collecting data from various sources by detecting patterns and outliers with the help of guided advanced analytics and visual navigation of data, thus enabling consolidation of all business information. Let’s say that you are a business owner, an analyst, a CIO, or a program manager.

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161