Juice Analytics

JULY 3, 2021

Then they documented the app building experience. Here’s what they had to say… It is a fierce rivalry: two friends, Owen and Marko, wanted to compare their Valorant statistics with each other to see who is truly the better player. To start, we looked up their statistics on Tracker.gg/Valorant. We needed to get to the facts.

Statistics 119

Statistics Visualization Measurement IT 119

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. They generally leverage simple statistical and analytical tools, but Power notes that some OLAP systems that allow complex analysis of data may be classified as hybrid DSS systems. Document-driven DSS.

Data mining 130

Data mining Data-driven Statistics OLAP 130

O'Reilly on Data

OCTOBER 18, 2022

If you’re thinking of a less formal internal assessment, the influential Closing the AI Accountability Gap puts forward a solid framework with worked documentation examples. A binary or numeric outcome allows for the application of traditional measures of practical and statistical significance with clear thresholds.

Risk Management 287

Risk Management Risk Testing Measurement 287

IBM Big Data Hub

FEBRUARY 13, 2024

For example, organizations can use generative AI to: Quickly turn mountains of unstructured text into specific and usable document summaries, paving the way for more informed decision-making. Generative AI uses advanced machine learning algorithms and techniques to analyze patterns and build statistical models.

Enterprise 120

Enterprise Modeling Testing Data-driven 120

Ontotext

APRIL 19, 2024

This depth of understanding of both statistical modeling and description and relationship logic of ontological modeling makes the company well suited to navigate the thicket of hybrid or neurosymbolic AI, in which statistical methods such as NLP and LLMs complement the symbolic logic in well-constructed knowledge graphs.

Metadata 52

Metadata Statistics Interactive Enterprise 52

IBM Big Data Hub

AUGUST 17, 2023

The process to create the commentary began by populating a data store on watsonx.data , which connects and governs trusted data from disparate sources (such as player rankings going into the match, head-to-head records, match details and statistics).

Unstructured Data 91

Unstructured Data Statistics Consulting Enterprise 91

O'Reilly on Data

MARCH 26, 2024

The prompts start the dream, and based on the LLM’s hazy recollection of its training documents, most of the time the result goes someplace useful. It takes the prompt and just returns one of the most similar “training documents” it has in its database, verbatim. Because, in some sense, hallucination is all LLMs do.

Modeling 271

Modeling Machine Learning Risk Advertising 271

IBM Big Data Hub

APRIL 13, 2023

Explore data In this step, I’ll look at both sample records and the summary statistics of the training dataset to gain insights into the dataset. outtable is the name of the table where SUMMARY1000 will store gathered statistics for the entire dataset. Check the summary statistics of the numeric column. NOT IN(SELECT FT.ID

Modeling 83

Modeling Statistics Machine Learning Testing 83

CIO Business Intelligence

OCTOBER 13, 2023

Data scientists are experts in applying computer science, mathematics, and statistics to building models. The US Bureau of Labor Statistics says there were 149,300 data architect jobs in the US in 2022 and projects the number of data architects will grow by 8% from 2022 to 2032. Are data architects in demand?

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

AWS Big Data

MARCH 13, 2024

RAG is a machine learning (ML) architecture that uses external documents (like Wikipedia) to augment its knowledge and achieve state-of-the-art results on knowledge-intensive tasks. We introduce the integration of Ray into the RAG contextual document retrieval mechanism. Open the CreateRayCluster document. json| jq '.data[].paragraphs[].qas[].question'

Data Processing 114

Data Processing Dashboards Machine Learning Management 114

Timo Elliott

DECEMBER 14, 2023

But if they’re “just” inaccurate, with the real data hidden behind a veil of noise, the result is still potentially useable with the right statistical techniques. For example, machine learning is already used to extract information from documents such as invoices: the date, amount, supplier ID etc.

Machine Learning 64

Machine Learning IoT Statistics Modeling 64

CIO Business Intelligence

AUGUST 14, 2023

Major finance and business information, along with sales and subcontracting documents, were processed manually and offline. Up until 2021, it often fell short – and for good reason. Even as the Huabao Group expanded, its digitization effort lagged. Nor was there a comprehensive understanding of changing consumer trends.

Key Performance Indicator 94

Key Performance Indicator Sales Manufacturing KPI 94

datapine

JANUARY 24, 2021

Additionally, incorporating a decision support system software can save a lot of company’s time – combining information from raw data, documents, personal knowledge, and business models will provide a solid foundation for solving business problems. There are basically 4 types of scales: *Statistics Level Measurement Table*.

IT 317

IT Statistics KPI Data-driven 317

O'Reilly on Data

MAY 18, 2020

And last is the probabilistic nature of statistics and machine learning (ML). Because statistics: Last is the inherently probabilistic nature of ML. Materiality is a widely used concept in the world of model risk management , a regulatory field that governs how financial institutions document, test, and monitor the models they deploy.

Risk 357

Risk Modeling Data Processing Software 357

O'Reilly on Data

NOVEMBER 29, 2022

The blueprint is an unenforceable document. That kind of granular approach would make it easier to develop statistical tests that could determine if the solution is harming any of the groups. The White House’s Office of Science and Technology Policy recently published the Blueprint for an AI Bill of Rights. Who will watch the watchmen?

Machine Learning 276

Machine Learning Recreation/Entertainment Risk Testing 276

CIO Business Intelligence

MARCH 14, 2024

AI has already found its way into many government departments, with the most common use of AI identified by the NAO being to support operational decision-making through automated document analysis, digital assistant functionality, and image recognition.

Testing 103

Testing Risk Digital Transformation Statistics 103

CIO Business Intelligence

JULY 6, 2023

Classic examples are the use of AI to capture and convert semi-structured documents such as purchase orders and invoices, Fleming says. We’re equipping this tool with a private ‘knowledge base’ of AT&T-specific data, with chat enabled to get answers directly from these internal AT&T documents and materials.”

Cost-Benefit 115

Cost-Benefit Technology Unstructured Data Testing 115

Alation

JULY 19, 2022

The catalog facilitates the synergy of the domain experts’ subject matter expertise with the data scientists statistical and coding expertise. Documenting data science projects this way in a data catalog saves time and prevents data scientists from wasting resources on duplicate projects.

Metadata 59

Metadata Data Quality Statistics Data Science 59

IBM Big Data Hub

APRIL 9, 2024

” The historical sources watsonx.data accesses comprise relational, object and document databases, including IBM® Db2® , IBM® Cloudant , IBM Cloud® Object Storage and PostgreSQL. “Rather than fine tuning the models through the tournament, we fine modify the input statistics that go into the models.

Management 80

Management IT Machine Learning Metrics 80

O'Reilly on Data

NOVEMBER 28, 2023

And there are tools for archiving and indexing prompts for reuse, vector databases for retrieving documents that an AI can use to answer a question, and much more. And there are many other applications for machine-generated text: AI is good at summarizing documents. It’s also well suited to writing a quick email.

Enterprise 267

Enterprise Modeling Testing Reporting 267

O'Reilly on Data

JUNE 18, 2019

Moreover, the domain knowledge, which often is not encoded in the data (nor fully documented), is an integral part of this data (see this article from Forbes). The good news is that researchers from academia recently managed to leverage that large body of work and combine it with the power of scalable statistical inference for data cleaning.

Machine Learning 255

Machine Learning Data Quality Statistics Modeling 255

Smart Data Collective

NOVEMBER 3, 2021

It refers to underwriting, customer onboarding, document management, analysis, and statistics. Due to interactive dashboards available on digital lending platforms, banks can monitor customer interactions, keep track of their risks and financial results, access document databases, and get relevant analytics.

Software 120

Software Data-driven Interactive Insurance 120

Smart Data Collective

MARCH 28, 2022

It can be further classified as statistical and predictive modeling, but the two are closely associated with each other. Data analytics greatly improves decision-making capabilities since they use valid data and statistics to arrive at a decision rather than going by blind faith.

Data Analytics 85

Data Analytics Software Analytics Statistics 85

Smart Data Collective

APRIL 15, 2021

Most will include documentation of data sources, the KPIs of the specific industry, the kind of reporting necessary, and whether or not the data flow will require automation. Previously, BI systems only presented statistical reports, but nowadays, interactive dashboards are available with customizable information. Develop a Strategy.

Business Intelligence 97

Business Intelligence Analytics Statistics Data Warehouse 97

IBM Big Data Hub

DECEMBER 4, 2023

The most common insurance use cases include optimizing processes that require processing large documents and large blocks of text or images. Customer engagement Providing insurance coverage involves working with numerous documents. IBM works with several insurance companies to identify high-value opportunities for using generative AI.

Insurance 54

Insurance Digital Transformation Risk Management Interactive 54

O'Reilly on Data

MARCH 24, 2020

HoloClean decouples the task of data cleaning into error detection (such as recognizing that the location “cicago” is erroneous) and repairing erroneous data (such as changing “cicago” to “Chicago”), and formalizes the fact that “data cleaning is a statistical learning and inference problem.”

Machine Learning 343

Machine Learning Statistics Data Quality Modeling 343

Smart Data Collective

SEPTEMBER 13, 2021

According to 2019 statistics, the average cost of a construction dispute was close to $19 million, and the length of seeing such a dispute to resolution was nearly 18 months. Improve Documentation. Construction analytics technology also helps ensure better documentation. Therefore, they will be held to higher standards.

Analytics 94

Analytics Cost-Benefit Big Data Statistics 94

CIO Business Intelligence

JANUARY 17, 2024

Additionally, the company has developed its own reporting engine, which provides advanced statistical analysis along with interactive dashboards and reports, using open standards such as HTML5, CSS3, JavaScript, D3.js js and React.js.

Digital Transformation 112

Digital Transformation Dashboards Reporting Data Science 112

CIO Business Intelligence

AUGUST 11, 2023

ALICE uses “word embedding” to go through contract documents paragraph by paragraph, looking for keywords to determine whether the paragraph relates to a particular contract clause type. NLTK is offered under the Apache 2.0 It was primarily developed at the University of Massachusetts Amherst.

Unstructured Data 139

Unstructured Data Modeling Machine Learning Data mining 139

datapine

SEPTEMBER 16, 2022

But often that’s how we present statistics: we just show the notes, we don’t play the music.” – Hans Rosling, Swedish statistician. Data Sketches is a publication that documents the creative process of authors Nadie Bremer and Shirley Wu in creating 24 data visualization projects. click for book source**.

Visualization 304

Visualization Dashboards Data-driven Statistics 304

DataRobot Blog

SEPTEMBER 1, 2022

Now you can aggregate prediction statistics much faster while controlling the governance and security of your sensitive data — no need to submit their entire prediction requests to DataRobot AI Cloud Platform to get data about drift and accuracy monitoring. See DataRobot MLOps in Action. Request a Demo.

Metrics 145

Metrics Statistics Modeling Data Science 145

Alation

OCTOBER 12, 2022

Traditional business analysis uses numerical methods to paint a picture, often through numerical methods, like statistics. What Is the Role of Statistics in Quantitative Data Analysis? Statistics is at the heart of quantitative analysis. Two of the most common types of inferential statistics are: Regression analysis.

Statistics 52

Statistics Sales Testing Marketing 52

FineReport

MAY 18, 2024

This technique helps identify correlations or patterns between variables and is widely used in statistical analysis and research studies. Box and Whisker Plots Boxplots and whisker plots offer a visual summary of the distribution of numerical data by displaying key statistical measures such as median, quartiles, and outliers.

Visualization 52

Visualization Interactive Cost-Benefit Dashboards 52

BizAcuity

APRIL 1, 2023

Widely used to discover trends, patterns, check assumptions and spot anomalies or outliers, EDA involves a variety of techniques including statistical analysis, and machine learning to gain a better understanding of data. OCR is widely used to digitize all kinds of physical documentation.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

FineReport

MARCH 6, 2024

What are Financial Statements Financial statements are written documents prepared regularly based on daily accounting data. The statistics of accounts receivable mainly serve as an estimate for future expected income. The date transaction report for payment channels primarily assists financial personnel in reconciling accounts.

Reporting 52

Reporting Operational Reporting Statistics Dashboards 52

DataKitchen

JANUARY 23, 2023

Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements. Data testing can be done through various methods, such as data profiling, Statistical Process Control, and quality checks.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Ontotext

FEBRUARY 9, 2023

Because a knowledge graph pulls together data from a variety of sources and a range of formats it can bring together information from news media, internal documents like emails or texts, along with traditional financial data subscriptions. A knowledge graph serves to document and automate that expertise.

Statistics 52

Statistics Technology Marketing Enterprise 52