datapine

MARCH 31, 2022

6) Main Players In The BI Industry. For example, if you enjoy computer science, programming, and data but are too extroverted to program all day long, you could work in a more human-oriented area of intelligence for business, perhaps involving more face-to-face interactions than most programmers would encounter on the job.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

IBM Big Data Hub

JUNE 13, 2022

These higher-risk areas can include uses of AI in employment, financial, law enforcement, and healthcare settings, as well as other areas where outcomes can have a significant impact to individuals and society [1]. The use of artificial intelligence (AI) is now commonplace throughout society. AI governance will require an agile approach.

Risk 98

Risk Risk Management Data-driven Metrics 98

Cloudera

FEBRUARY 8, 2021

Continuing from my previous blog post about how awesome and easy it is to develop web-based applications backed by Cloudera Operational Database (COD), I started a small project to integrate COD with another CDP cloud experience, Cloudera Machine Learning (CML). . For this purpose, I will use the LSTM (Long Short-term memory) algorithm.

Machine Learning 72

Machine Learning Statistics Modeling Dashboards 72

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. Our Top Data Science Tools.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Ontotext

MARCH 8, 2023

Here, I will draw upon our own experience from client projects and lessons learned to provide a selection of optimal use cases for knowledge graphs and semantic solutions along with real world examples of their applications. Several factors are driving the adoption of knowledge graphs. How do we get better with understanding our customers?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

CIO Business Intelligence

MARCH 25, 2022

Last December, Broadcom Software published our blog: Predictions for 2022. We will now explore each of these in more depth in our next blog series. It was a data-centric model where you don’t trust anything going on inside or outside of the perimeter. First up, Zero Trust. Prediction: Zero Trust becomes table stakes.

Software 52

Software Risk Strategy Reporting 52

datapine

SEPTEMBER 29, 2022

6) Data Quality Metrics Examples. 6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. Table of Contents. 1) What Is Data Quality Management? 2) Why Do You Need DQM? With a shocking 2.5

Data Quality 241

Data Quality Metrics Data-driven Management 241

IBM Big Data Hub

JULY 19, 2023

Some examples of potential use cases for generative AI in life sciences include but are not limited to: AI for Medical Legal Review (MLR) : Increasing globalization and exponential growth in digital marketing techniques has been putting strain on the already complex, time consuming and challenging process.

Consulting 63

Consulting Machine Learning Manufacturing Optimization 63

Cloudera

SEPTEMBER 20, 2022

This blog is intended to serve as an ethics sheet for the task of AI-assisted comic book art generation, inspired by “ Ethics Sheets for AI Tasks.” AI-assisted comic book art generation is a task I proposed in a blog post I authored on behalf of my employer, Cloudera. Introduction. Scope, motivation, and benefits.

Deep Learning 85

Deep Learning Cost-Benefit Risk Data-driven 85

Domino Data Lab

JULY 19, 2021

Who takes responsibility for the operationalized models? Develop: The Develop stage is where data scientists build and assess various models based on a variety of different modeling techniques. Data scientists create a model and test it with algorithms and data. The Enterprise MLOps Process Overview. Data Scientist.

Enterprise 85

Enterprise Data Science Testing Modeling 85

datapine

JANUARY 24, 2021

For example, you need to develop a sales strategy and increase revenue. In our cutthroat digital age, the importance of setting the right data analysis questions can define the overall success of a business. That being said, it seems like we’re in the midst of a data analysis crisis. This quote might sound a little dramatic.

IT 317

IT Statistics KPI Data-driven 317

DataRobot Blog

MAY 26, 2022

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. Validating Machine Learning Models. If we have already built out a model for a business application, how do we ensure that it is working to our expectations?

Risk 52

Risk Modeling Metrics Business Objectives 52

bridgei2i

JUNE 23, 2021

6 Ways AI Is Taking The Insurance Industry Into The Future. For example, the insurance industry is witnessing a strong acceleration in the adoption and growth of AI for task automation, improvement of service quality, and data-driven decision making. Insurance is a resource-intensive field. Insurance is a resource-intensive field.

Insurance 52

Insurance Risk Deep Learning Data-driven 52

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. These examples are well covered by many others (e.g.,

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Sisense

APRIL 10, 2020

In this article, we discuss how this data is accessed, an example environment and set-up to be used for data processing, sample lines of Python code to show the simplicity of data transformations using Pandas and how this simple architecture can enable you to unlock new insights from this data yourself. Let’s get started.

Visualization 105

Visualization Reporting Data Processing Dashboards 105

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues. Just one of these problems can prove costly to an organization.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

The Data Visualisation Catalogue

APRIL 4, 2019

Andy will also demonstrate how VR can be useful in multi-dimensional data analysis and in the financial industry. I’ve implemented DataView in my own work and find it an excellent way to organize investment information, do data discovery and create predictive models. Below is a guest post from Andy Maggio, the founder of DataView VR.

Dashboards 73

Dashboards Predictive Modeling Visualization Modeling 73

Ontotext

JANUARY 10, 2020

million financial transactions in mind, sorry – in a graph, it might well be. In the era of bots serving as investment vehicles and plenty of platforms offering tools for automated investing, could it be that the strength of investment strategies soon becomes a matter of computing power and algorithms well-built? But we will be wrong.

Data mining 59

Data mining Machine Learning Data-driven Marketing 59

Occam's Razor

JUNE 4, 2018

Yes, that additional $6 mil is not as hard to accomplished for an imaginative focused team – in fact you can get that from implementing half of the recommendations in this blog post. By every indicator available, ecommerce is continuing to grow at an insane speed. youarekillingme. Yet, when I want to pay full price on www.timbuk2.com

Strategy 124

Strategy Cost-Benefit Testing Sales 124

datapine

MARCH 25, 2022

6) BI And BA Examples. While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. Table of Contents. 2) BI vs BA As Seen Through Football.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Occam's Razor

JANUARY 24, 2011

Regular readers of this blog will recognize that I suffer from OOD. The other way OOD manifests itself is that I am in your face, on this blog, constantly asking you to create goals in your web analytics tool ( macro and micro conversions ) as well as identify goal values for each of those beloved goals. Here is an example.

Analytics 122

Analytics Finance B2B ROI 122

O'Reilly on Data

MARCH 23, 2023

It’s important to understand that ChatGPT is not actually a language model. It’s a convenient user interface built around one specific language model, GPT-3.5, It’s a convenient user interface built around one specific language model, GPT-3.5, The GPT-series LLMs are also called “foundation models.” It’s much more.

IT 262

IT Modeling Testing Risk 262

Domino Data Lab

JANUARY 6, 2019

And my favorite topic: what are some of the best books, blogs, podcasts, etc., If you’re looking for good examples of data science curriculum, for example to help train your team, where would you start? Also, clearly there’s no “one size fits all” educational model for data science. Introduction. Learning Data Science.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

datapine

OCTOBER 21, 2020

We will then look at 18 big data examples in healthcare that already exist and that medical-based institutions can benefit from. Download our free bite-sized summary and see our top examples! Now that we live longer, treatment models have changed and many of these changes are namely driven by data.

Big Data 364

Big Data Data Analytics Analytics Cost-Benefit 364

IBM Big Data Hub

FEBRUARY 19, 2024

Financial benefits include increased revenue through the creation of adjacent industry business models, accessing new markets to establish more revenue streams, and growing existing revenue. In 2023, the global data monetization market was valued at USD 3.5 billion, and experts project it to reach USD 14.4 from 2024 to 2032.

Cost-Benefit 69

Cost-Benefit Data-driven Optimization Marketing 69

IBM Big Data Hub

APRIL 3, 2024

Take last year’s US Open , for example, where IBM watsonx™ projected the level of advantage or disadvantage of all players in the singles draw. These examples go hand-in-hand with rapid enterprise adoption. For instance, we are working together with Adobe to embed watsonx into their platform to support key industries.

Enterprise 66

Enterprise Data-driven Machine Learning Modeling 66

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. This is like a denial-of-service (DOS) attack on your model itself.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Of particular interest to LSOS data scientists are modeling and prediction techniques which keep improving with more data. Of particular interest to LSOS data scientists are modeling and prediction techniques which keep improving with more data.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

IBM Big Data Hub

APRIL 3, 2024

On March 6, 2024, the US Securities and Exchange Commission (SEC) adopted rules to enhance and standardize climate-related disclosures by public companies and in public offerings. The commission’s adoption of the rules is two years in the making.

Risk 56

Risk Gap analysis Reporting Risk Management 56

IBM Big Data Hub

FEBRUARY 15, 2024

It refers to a set of metrics used to measure an organization’s environmental and social impact and has become increasingly important as it relates to a company’s business model, risk management strategy , reporting requirements and more. So, how can companies stay ahead of the curve?

Reporting 83

Reporting Consulting Risk Metrics 83

AWS Big Data

AUGUST 2, 2023

In this blog, we will walk through how we can apply existing enterprise data to better understand and estimate Scope 1 carbon footprint using Amazon Simple Storage Service (S3) and Amazon Athena , a serverless interactive analytics service that makes it easy to analyze data using standard SQL. More information on CEMS is available here.

Data Lake 72

Data Lake Measurement Visualization Data Architecture 72

datapine

MAY 31, 2022

Table of Contents. 1) What Is Cloud Computing? 2) The Challenges Of Cloud Computing. 3) Cloud Computing Benefits. 4) The Future Of Cloud Computing. Everywhere you turn these days, “the cloud” is being talked about. It’s a hot topic, and as technologies continue to evolve at a rapid pace, the scope of the cloud continues to expand.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

IBM Big Data Hub

AUGUST 11, 2023

For example, moving to a modern customer relationship management (CRM) platform from spreadsheets and/or decentralized records may incur an initial cost, but it can increase efficiency and drive sales. And technology budgets are rising commensurate to this new reality. IT spending is expected to increase to $4.6 from 2022.

Management 80

Management IT Forecasting Software 80

datapine

MAY 11, 2022

“By visualizing information, we turn it into a landscape that you can explore with your eyes. A sort of information map. And when you’re lost in information, an information map is kind of useful.” – David McCandless. Did you know? 90% of the information transmitted to the brain is visual. back on every dollar spent.

Visualization 252

Visualization Dashboards Key Performance Indicator Sales 252

Cloudera

MAY 18, 2021

Speed matters in financial markets. Whether the goal is to maximize alpha or minimize exposure, financial technologists invest heavily in having the most up-to-date insights on the state of the market and where it is going. In case you missed it, part I starts with a simple case of calculating streaming VWAP. Intraday VaR.

Risk 94

Risk Marketing Risk Management Data-driven 94

datapine

NOVEMBER 13, 2019

It doesn’t matter how innovative your brand is or how groundbreaking your business model might be; if your business is ridden with glaring inefficiencies, your potential for growth is eventually going to get stunted. Download our guide to find out about the power of procurement reports! What Are Procurement Reports?

Reporting 158

Reporting KPI Cost-Benefit Metrics 158

Ontotext

DECEMBER 9, 2020

We all want to solve the interesting data challenges, build analytics, generate graph embeddings and train smart machine learning models over our knowledge graph data. Generate a semantic object model from existing RDF schemas. Perhaps it’s something like the Star Wars schema I discussed in my previous blog posts.

Modeling 130

Modeling Management Optimization Metrics 130