David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

Data Science 340

Data Science Data Lake Data mining Deep Learning 340

IBM Big Data Hub

AUGUST 15, 2022

Sometimes as data scientists, we are often so determined to build a perfect model that we can unintentionally include human bias into our models. Often the bias creeps in through training data and then is amplified and embedded in the model. Model risk management.

Data mining 60

Data mining Risk Modeling Risk Management 60

Jet Global

JUNE 5, 2019

So how does a leading-edge business find a way to marry their wealth of data with the opportunity to utilize it effectively via BI software? Let’s introduce the concept of data mining. Toiling Away in the Data Mines. Clustering helps to group data and recognize differences and similarities.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

Analytics Vidhya

JANUARY 28, 2022

This article was published as a part of the Data Science Blogathon. Image Source: Author Introduction Data Engineers and Data Scientists need data for their Day-to-Day job. Of course, It could be for Data Analytics, Data Prediction, Data Mining, Building Machine Learning Models Etc.,

Data Science 261

Data Science Data mining Machine Learning Publishing 261

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Business analytics is a subset of data analytics. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

O'Reilly on Data

JANUARY 22, 2019

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. Clearly, a map will not be able to capture the richness of the terrain it models.

Modeling 135

Modeling Finance Uncertainty Data mining 135

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. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 144

Data mining Data-driven Statistics OLAP 144

Jen Stirrup

SEPTEMBER 30, 2021

They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way. They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way. Excel specialists may know that Excel also has a series of Data Mining Add-ins.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

datapine

JANUARY 24, 2021

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. That being said, it seems like we’re in the midst of a data analysis crisis.

IT 317

IT Statistics KPI Data-driven 317

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. The exam consists of 65 multiple-choice or multiple-response questions, which the candidate has 180 minutes to complete.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

CIO Business Intelligence

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Smart Data Collective

MAY 16, 2022

Data is becoming more important to modern organizations than ever before. One poll found that 74% of companies feel they are still struggling to use data effectively. One of the problems is that they don’t manage their data well. How Companies Can Manage their Data Better.

Management 127

Management Data mining Data Warehouse Data Collection 127

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Financial services: Develop credit risk models. from 2022 to 2028.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

Decision Management Solutions

JUNE 4, 2021

Like many enterprises, you’ve likely made a hefty investment in analytic technology—from interactive dashboards and advanced visualization tools to data mining, predictive analytics, machine learning (ML), and artificial intelligence (AI). 1 MIT Sloan Management Review September 06, 2017.

Analytics Technologies 52

Analytics Technologies Technology Modeling Key Performance Indicator 52

Smart Data Collective

AUGUST 30, 2022

There are many important applications of data analytics technology. Analytics can use existing data to model scenarios where customers will respond to different prices. This article will walk you through 5 top B2B pricing models that you should consider when determining your own strategy. Value-Based Pricing.

B2B 131

B2B Analytics Cost-Benefit Metrics 131

Analytics Vidhya

DECEMBER 27, 2023

Introduction Data annotation plays a crucial role in the field of machine learning, enabling the development of accurate and reliable models. In this article, we will explore the various aspects of data annotation, including its importance, types, tools, and techniques.

Machine Learning 270

Machine Learning Modeling Analytics Data mining 270

Smart Data Collective

MARCH 2, 2023

Big data technology used to be a luxury for small business owners. In 2023, big data Is no longer a luxury. One survey from March 2020 showed that 67% of small businesses spend at least $10,000 every year on data analytics technology. They can use data mining tools to evaluate the average interest rate of different lenders.

Big Data 81

Big Data Uncertainty Risk Data mining 81

CIO Business Intelligence

JUNE 28, 2023

“These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As Belcorp operates under a direct sales model in 14 countries. The team leaned on data scientists and bio scientists for expert support.

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

BizAcuity

MAY 7, 2019

Today, several businesses, especially those belonging to the FMCG sector, have sophisticated demand forecasting models in place, which help them stay ahead of the market. An area of predictive analytics, demand forecasting takes into account the historical data of a business and uses that to harnesses the demand for their goods and services.

Forecasting 75

Forecasting IT Sales Statistics 75

Smart Data Collective

JUNE 15, 2021

Data-driven organizations are looking for new ways to use data technology to improve their operations. Big data can play a very important role in solving these challenges. Pre-employment screening with data mining tools increases the quality of candidates. One bad hire can cost a company quite a lot.

Data-driven 129

Data-driven Data mining Cost-Benefit Big Data 129

Smart Data Collective

AUGUST 30, 2022

Cloud technology results in lower costs, quicker service delivery, and faster network data streaming. It also allows companies to offload large amounts of data from their networks by hosting it on remote servers anywhere on the globe. Data backup is one of the most important benefits of cloud computing. Multi-cloud computing.

Technology 133

Technology Enterprise Cost-Benefit Testing 133

Smart Data Collective

NOVEMBER 1, 2020

If you have labeled training data that you can use as a training example, we’ll call it supervised machine learning. Unlike supervised ML, we do not manage the unsupervised model. From a technical standpoint, it implies a set of techniques for cutting down the number of input variables in training data.

Machine Learning 133

Machine Learning Data mining Visualization Statistics 133

CIO Business Intelligence

AUGUST 11, 2023

Transformer models take applications such as language translation and chatbots to a new level. Innovations such as the self-attention mechanism and multi-head attention enable these models to better weigh the importance of various parts of the input, and to process those parts in parallel rather than sequentially.

Unstructured Data 142

Unstructured Data Modeling Machine Learning Data mining 142

Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. Honestly, KDD has been promoting data science way before data science was even cool. 1989 to be exact. The details are below.

KDD 81

KDD Knowledge Discovery Data mining Statistics 81

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. Business intelligence analyst job requirements BI analysts typically handle analysis and data modeling design using data collected in a centralized data warehouse or multiple databases throughout the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

Smart Data Collective

DECEMBER 19, 2021

That’s because the machine learning projects go through and process a lot of data, and that data should come in the specified format to make it easier for the AI to catch and process. Likewise, Python is a popular name in the data preprocessing world because of its ability to process the functionalities in different ways.

Optimization 135

Optimization Machine Learning Data mining Statistics 135

CIO Business Intelligence

JANUARY 19, 2024

Data scientist is one of the hottest jobs in IT. Companies are increasingly eager to hire data professionals who can make sense of the wide array of data the business collects. The exam is designed for seasoned and high-achiever data science thought and practice leaders.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

Smart Data Collective

NOVEMBER 12, 2021

However, there are a lot of other benefits of big data that have not gotten as much attention. Over overlooked advantage of big data is that it can help improve outsourcing strategies. We talked about the benefits of outsourcing IoT and other data science obligations. Access to Extensive Talent Pipelines with Data Mining.

Data-driven 103

Data-driven Cost-Benefit Data mining Big Data 103

CIO Business Intelligence

OCTOBER 13, 2023

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

Smart Data Collective

APRIL 19, 2022

Data mining technology has become very important for modern businesses. Companies use data mining technology for a variety of purposes. One of the most important is collecting revenue data to draft financial statements, forecast future sales and make decisions to address revenue shortfalls.

Sales 106

Sales Reporting Data mining Forecasting 106

Jen Stirrup

OCTOBER 14, 2019

SQL Server is one of the most mature, well-known and common databases in the world, according to data from DB-Engines ranking. Generally speaking, the cloud is attractive to businesses due to its lower costs, scalability and pay-as-you-go pricing model. It’s written by William McKnight and Jake Dolezal from GigaOm.

Data mining 67

Data mining IT Business Intelligence Testing 67

Smart Data Collective

JUNE 14, 2022

We’ve put together some ideas to help you along the way so that you can grow your business with big data. Big data has made it easier than ever to create excellent websites. Since big data makes the process more efficient, it should be easy to do both. However, it doesn’t come without its difficulties. Build the Perfect Website.

Big Data 104

Big Data Data mining Metrics Sales 104

Smart Data Collective

NOVEMBER 11, 2021

We have frequently talked about the merits of using big data for B2C businesses. One of the reasons that we focus on these sectors is that there is so much data on consumers, which makes it easier to create a solid business model with big data. It can be even more useful if you use it with big data.

B2B 112

B2B Data mining Big Data Marketing 112

Smart Data Collective

JUNE 23, 2022

The right data analytics tools can be very valuable. Finally, if your company is paying for office space through renting, it may be worth adopting a hybrid working model and only using communal workspaces on the days you need to get together. Data analytics tools make it easier to take a deep dive into your finances.

Analytics 104

Analytics Data mining Finance Insurance 104

Rocket-Powered Data Science

JULY 7, 2019

Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…). Examples: Cars, Trucks, Taxis. They cannot process language inputs generally.

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 121

Predictive Analytics Analytics Predictive Modeling Data mining 121

Ontotext

DECEMBER 20, 2023

The answer is through the wealth of object, text and image data, which serve as a reference to olfactory experiences. It’s these data that the Odeuropa project aimed to tame by developing methods for identifying and tracing olfactory reference and also by designing a data model to represent olfactory knowledge.

Visualization 78

Visualization Data Processing Data mining Interactive 78