Smart Data Collective

OCTOBER 8, 2021

Modern machine learning and back-testing; how quant hedge funds use it. This is according to Barclay Hedge founder and President Sol Waksman in his July 2018 statement. Similarly, hedge funds often use modern machine learning and back-testing to analyze their quant models. Mathematical Model-based Strategies.

Machine Learning 115

Machine Learning Testing Strategy Modeling 115

CIO Business Intelligence

JANUARY 5, 2024

Then in March, the pandemic hit and hotel activity stopped, but it gave us the chance to accelerate the company’s transformation and digitalization process that started in 2018 with a five-year plan. From an organizational standpoint, we evolved to a nearshore model, attracting the necessary talent that new technologies required.

IT 107

IT Finance Cost-Benefit Strategy 107

Smart Data Collective

JANUARY 27, 2021

Conversely, if predictive analytics models suggest that the value of a cryptocurrency price is likely to decrease, more investors are likely to sell off their cryptocurrency holdings. They tended to avoid using technical analysis models, because those models don’t tend to hold up well with traditional securities, such as stocks and bonds.

Machine Learning 139

Machine Learning Forecasting Predictive Analytics Marketing 139

CIO Business Intelligence

JULY 5, 2022

Research firm Gartner defines business analytics as “solutions used to build analysis models and simulations to create scenarios, understand realities, and predict future states.”. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 126

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 126

Smart Data Collective

AUGUST 9, 2022

The number increased 56% between 2017 and 2018. The main difference between the agile approach and waterfall methodology is that Agile relies on continuous development and testing, whereas waterfall methodology is a linear life cycle. This can be achieved through penetration testing, simulated attacks, and application scanning.

Big Data 112

Big Data Technology Testing Cost-Benefit 112

Sisense

JANUARY 14, 2021

VP of Business Intelligence Michael Hartmann describes the problem: “When an upstream data model change was introduced, it took a few days for us to notice that one of our Sisense charts was ‘broken.’ With that in mind, the developers at Billie came up with the idea to automatically test Sisense charts.

Dashboards 85

Dashboards Testing Business Intelligence Interactive 85

CIO Business Intelligence

MARCH 7, 2024

Greg Beltzer has been beta testing key generative AI technologies for the past six months and is eager to capitalize on them when released this spring. My strategy was to put Salesforce at the center,” says Beltzer, who helped launched RBC US’s journey to Microsoft Azure and AWS in 2018 when he joined the company.

Enterprise 124

Enterprise Software Testing Interactive 124

CIO Business Intelligence

FEBRUARY 14, 2023

Meanwhile, through 2017 and 2018, he says, “there was a big surge in companies moving from usually on-premises data centers to AWS or Azure, and then finding a partner to run their SAP in the cloud. We had to do a lot of functional testing to make sure.” And the argument in favor of the brownfield migration has stood the test.

Data Processing 98

Data Processing Cost-Benefit Testing Modeling 98

CIO Business Intelligence

NOVEMBER 1, 2023

And alongside these major changes, Volvo is also resetting its business model and switching to direct sales in that part of the network of global dealers broadens their roles where instead of just selling Volvo cars, they become distributors. But even with great advantages came disadvantages.

Software 126

Software Testing Digital Transformation Management 126

Domino Data Lab

JUNE 13, 2019

Recently, Chhavi Yadav (NYU) and Leon Bottou (Facebook AI Research and NYU) indicated in their paper, “ Cold Case: The Lost MNIST Digits ”, how they reconstructed the MNIST (Modified National Institute of Standards and Technology) dataset and added 50,000 samples to the test set for a total of 60,000 samples. Did they overfit the test set?

Testing 83

Testing Data Science Experimentation Metadata 83

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. 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.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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). Azure Text Analytics. Stanford Core NLP.

Deep Learning 227

Deep Learning Testing Machine Learning Modeling 227

Corinium

JUNE 6, 2019

Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. It is also important to have a strong test and learn culture to encourage rapid experimentation. Fractal’s 2018 Net Promoter Score is greater than 70.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Domino Data Lab

MAY 15, 2019

Unfortunately, a common challenge that many industry people face includes battling “ the model myth ,” or the perception that because their work includes code and data, their work “should” be treated like software engineering. I was fortunate to see an early iteration of Pete Skomoroch ’s ML product management presentation in November 2018.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

Smart Data Collective

MARCH 8, 2021

The total amount of new data will increase to 175 zettabytes by 2025 , up from 33 zettabytes in 2018. Thanks to the availability of comparative data for practically every type/model of a vehicle, fleet managers can plan maintenance activities based on certain knowledge. Such data is great for introducing revamped maintenance practices.

Big Data 143

Big Data Management Predictive Analytics Statistics 143

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Birst BI

AUGUST 23, 2018

For example, there are a plethora of software tools available to automatically develop predictive models from relational data, and according to Gartner, “By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.” [1] Source: Gartner (April 2018).

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Jen Stirrup

FEBRUARY 1, 2023

The effects of AI will be magnified in the coming decade as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning.

Recreation/Entertainment 62

Recreation/Entertainment Testing Advertising Insurance 62

CIO Business Intelligence

MAY 11, 2022

Loura joined Lumentum in October of 2018, bringing with him three decades of IT leadership experience. And that happens in a Socratic model where there are often people kind of at odds with each other. And then we are trying to create a bit of an incubator to go solve those problems, test those solutions out.

Sales 78

Sales Cost-Benefit Manufacturing Optimization 78

CIO Business Intelligence

MARCH 31, 2023

The exam will test your knowledge in seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. The exam was developed using the Agile Extension to the BABOK guide and was released in May 2018.

Business Analysis 88

Business Analysis Testing Business Analytics Statistics 88

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. Using ML models to search more effectively brought the search space down to 102—which can run on modest hardware. Program Synthesis Papers at ICLR 2018 ” – Illia Polosukhin (2018-05-01). Introduction.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

CIO Business Intelligence

MAY 18, 2023

By defining team types, their fundamental interactions, and the science behind them, you learn how to better model your organizations according to these definitions. We need to really understand the drivers that influence customer and employee trust, as this is increasingly a litmus test,” says Johnson.

IT 115

IT Software Recreation/Entertainment Technology 115

datapine

OCTOBER 21, 2020

Now that we live longer, treatment models have changed and many of these changes are namely driven by data. Every patient has his own digital record which includes demographics, medical history, allergies, laboratory test results, etc. and could provide a model for the EU to follow. 2) Electronic Health Records (EHRs).

Big Data 364

Big Data Data Analytics Analytics Cost-Benefit 364

Cloudera

DECEMBER 11, 2020

That compares to only 36 percent of customer interactions as of December 2019, which was before the pandemic impacted business, and only 20 percent in May 2018. Insurance and finance are two industries that rely on measuring risk with historical data models. Data Variety.

Insurance 93

Insurance Digital Transformation Unstructured Data Machine Learning 93

AWS Big Data

DECEMBER 8, 2023

In 2021, FanDuel’s workloads almost tripled since they first started using Amazon Redshift in 2018, and they started evaluating Redshift RA3 nodes vs. DC2 nodes to take advantage of the storage and compute separation and deliver better performance at lower costs.

Data Warehouse 67

Data Warehouse Cost-Benefit KPI Risk 67

AWS Big Data

FEBRUARY 1, 2024

Large language models (LLMs) are becoming increasing popular, with new use cases constantly being explored. This is where model fine-tuning can help. Before you can fine-tune a model, you need to find a task-specific dataset. Next, we use Amazon SageMaker JumpStart to fine-tune the Llama 2 model with the preprocessed dataset.

Metadata 96

Metadata Modeling Data Processing Unstructured Data 96

Smart Data Collective

MARCH 23, 2022

The ADA is modeled after the Civil Rights Act of 1964 in that it ensures that people with mental or physical disabilities are not discriminated against in the workplace while purchasing goods and services and when participating in state and local government programs and services. Morris points out that AI helps with automated testing.

Cost-Benefit 102

Cost-Benefit Data mining Sales Testing 102

AWS Big Data

AUGUST 10, 2023

You had to model, check, and understand the JSON and enter parameters manually without the option to validate them before triggering a workflow. For your ad hoc, testing, or custom runs, this simplifies the DAG’s parameter entry. you could provide parameters in JSON structure through the Airflow UI for custom workflow runs.

Management 75

Management Software Testing Modeling 75

CDW Research Hub

JUNE 10, 2021

With our acquisition of Forsythe in 2018, Sirius vaulted to the top ranks of security solution providers and our dedicated Security practice now contributes over $800 million to our annual revenue. Vulnerability Assessments & Testing. Model Alignment & Implementation. Add our strengths to your security strategy.

Enterprise 52

Enterprise Consulting Risk Business Objectives 52

Insight

MARCH 20, 2020

There is a negative feedback loop that commonly occurs when something goes wrong in validation, testing or production which requires redesigns, product recalls, as well as a loss of employee time and company profit. Then they used a Conditional Wasserstein GAN (Generative Adversarial Network)to generate the 3D models from the text embeddings.

Interactive 143

Interactive Modeling Machine Learning Testing 143

Cloudera

MAY 15, 2018

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. Derman (2016), Cesa (2017) & Bouchard (2018)).

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Jet Global

OCTOBER 19, 2020

In 2018, Microsoft announced the launch of D365 BC to replace several of its legacy products (Microsoft Dynamics NAV and Microsoft Dynamics GP). In performance testing, the new adapter cut processing time in half. The new adapter has been tested for multiple locales and languages. Data retrieval is significantly faster.

Data Warehouse 98

Data Warehouse Analytics Reporting Testing 98

O'Reilly on Data

NOVEMBER 28, 2023

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. 16% of respondents working with AI are using open source models. A few have even tried out Bard or Claude, or run LLaMA 1 on their laptop.

Enterprise 271

Enterprise Modeling Testing Reporting 271

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. 2018-06-21). Introduction.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Insight

FEBRUARY 13, 2019

In late 2018, Google open-sourced BERT, a powerful deep learning algorithm for natural language processing. This allows BERT to provide significantly higher performance than models that are only able to leverage a small task-specific dataset. Download the BERT model files. Prior to Insight, he was at IBM Watson. Run training.

Testing 72

Testing Machine Learning Deep Learning Modeling 72

CIO Business Intelligence

MAY 17, 2022

If a correlation uncovered by the algorithm is weak, doctors might be subjecting patients to unnecessary tests that would be a waste of time and money for the hospital. Since the law took effect in 2018, more than 1,100 fines have been issued, and the totals keep going up. Was the problem in the model, or in its implementation?

Risk 142

Risk Consulting Machine Learning Data Science 142

datapine

NOVEMBER 27, 2019

Another increasing factor in the future of business intelligence is testing AI in a duel. The predictive models, in practice, use mathematical models to predict future happenings, in other words, forecast engines. However, businesses today want to go further and predictive analytics is another trend to be closely monitored.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361