Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. These data models predict outcomes of new data. Programming knowledge is needed for the typical tasks of transforming data, creating graphs, and creating data models. Basics of Machine Learning. Where to start? The Fundamentals. Mathematics.

E-Commerce 262

E-Commerce Cloud Computing Big Data Data Modelling 262

ElegantJ BI

MAY 31, 2021

Machine Maintenance is always cheaper then downtime! Sooner or later, all machines run to fail and monitoring the condition of the machine is crucial for any enterprise as any unplanned downtime can have greater economic impact resulting in reduced productivity and ultimately losing the customers.

Logistics 130

Logistics Visualization Monitoring Planning 130

ElegantJ BI

MAY 31, 2021

Machine Maintenance is always cheaper then downtime! Sooner or later, all machines run to fail and monitoring the condition of the machine is crucial for any enterprise as any unplanned downtime can have greater economic impact resulting in reduced productivity and ultimately losing the customers.

Logistics 130

Logistics Visualization Monitoring Planning 130

Smart Data Collective

NOVEMBER 1, 2020

Hence, it comes as no surprise that mundane business tasks are being completely taken over by tech advancements. Machines, artificial intelligence (AI), and unsupervised learning are reshaping the way businesses vie for a place under the sun. What Is Unsupervised Machine Learning? Unsupervised ML: The Basics.

Data Mining 335

Data Mining Visualization Artificial Intelligence Digital 335

Smart Data Collective

JUNE 7, 2019

Task management applications are changing the way we manage teams. Here are some of the primary benefits of these task management applications : Task management tools improve team productivity. Task management tools make sure that teams operate more efficiently. Task management tools minimize worker stress.

Artificial Intelligence 195

Artificial Intelligence Project Management Logistics Monitoring 195

Marutitech

DECEMBER 17, 2021

Predictive analytics tools comprise various models and algorithms, with each predictive model designed for a specific purpose. Identifying the best predictive analytics model for your business is a crucial part of business strategy. You must be wondering what the different predictive models are?

Predictive Analytics 140

Predictive Analytics Data Mining Finance Data Analytics 140

ElegantJ BI

FEBRUARY 8, 2021

Smarten provides us a feature of Smarten Assisted Predictive Modelling which reduces the time and skills required to produce accurate, clear results, quickly using machine learning. Furthermore, it is always more difficult and expensive to acquire a new customer than it is to retain a current paying customer.

Visualization 130

Visualization Monitoring Data Analytics Data Analytics 130

ElegantJ BI

FEBRUARY 8, 2021

Smarten provides us a feature of Smarten Assisted Predictive Modelling which reduces the time and skills required to produce accurate, clear results, quickly using machine learning. Furthermore, it is always more difficult and expensive to acquire a new customer than it is to retain a current paying customer.

Visualization 130

Visualization Monitoring Data Analytics Data Analytics 130

ElegantJ BI

FEBRUARY 8, 2021

Smarten provides us a feature of Smarten Assisted Predictive Modelling which reduces the time and skills required to produce accurate, clear results, quickly using machine learning. Classification. Steps to Open a loaded dataset in Smarten : Go to Open -> Data in top right dropdown in Smarten. Examine the dataset.

Visualization 130

Visualization Monitoring Data Analytics Data Analytics 130

Astera

MAY 6, 2024

– Quick and easy to learn. – Limited capabilities; suitable only for basic tasks. Python libraries, R) – Sophisticated algorithms for complex tasks. – Comprehensive machine learning capabilities. – Steeper learning curve; requires coding skills. Advanced Tools (e.g.,

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Analysts Corner

SEPTEMBER 25, 2023

In this comprehensive guide, we will delve into the concept of regression analysis, explore various types of regression techniques, discuss their assumptions and limitations, and provide practical tips for implementing and optimizing regression models to derive meaningful insights from data.

Logistics 130

Logistics Healthcare Vision Finance 130

ElegantJ BI

JANUARY 24, 2019

What is Automated Machine Learning? With the right tools, today’s average business user can become a Citizen Data Scientist , using data integrated from various sources to learn, test theories and make decisions. Take for example, the task of performing predictive analytics.

Predictive Analytics 130

Predictive Analytics Embedded Analytics Planning Visualization 130

ElegantJ BI

JANUARY 24, 2019

What is Automated Machine Learning? With the right tools, today’s average business user can become a Citizen Data Scientist , using data integrated from various sources to learn, test theories and make decisions. Take for example, the task of performing predictive analytics.

Predictive Analytics 130

Predictive Analytics Embedded Analytics Planning Visualization 130

ElegantJ BI

JANUARY 24, 2019

What is Automated Machine Learning? With the right tools, today’s average business user can become a Citizen Data Scientist , using data integrated from various sources to learn, test theories and make decisions. Take for example, the task of performing predictive analytics.

Predictive Analytics 130

Predictive Analytics Embedded Analytics Planning Visualization 130

Cprime

FEBRUARY 16, 2021

The massive outbreak in the generation of data has propelled advancements in the fields of machine learning and artificial intelligence. This post discusses the purpose and difference between machine learning and data mining. What is machine learning? Differences between data mining and machine learning.

Data Mining 94

Data Mining Artificial Intelligence 94

Marutitech

OCTOBER 8, 2021

With advancements in technology and fields like deep learning, sentiment analysis is becoming more and more common for companies that want to gauge their customers’ sentiments. ’, its tools, and different classifications and use cases. . However, below are some of the popular sentiment analysis classifications: 1.

Monitoring 98

Monitoring Documentation Logistics Customer Experience 98

Analysts Corner

SEPTEMBER 28, 2023

We are finishing this year’s projects, heading to the final push before some time off over the holiday season; and as a result we learn a lot and share this knowledge. When we eventually encounter those tasks, we either perform them — thereby exceeding our estimates — or skip them, possibly compromising quality in the process. >

Enterprise Architecture 130

Enterprise Architecture Artificial Intelligence Logistics Process Modelling 130

Marutitech

AUGUST 18, 2021

Computer vision uses specialized methods and general recognition algorithms, making it the subfield of artificial intelligence and machine learning. Traditional computer vision techniques follow the top-down flow for identifying the image using its features, whereas deep learning models work vice versa.

Vision 98

Vision Visualization Artificial Intelligence Digital 98

Marutitech

APRIL 7, 2022

When historical data that has been input into the system is studied using a mathematical model, the result can lead to suitable operational adjustments. Given the development of the Python framework in recent years, owing to its simplicity and capabilities, anyone can build a competitive predictive analytics model using Python.

Predictive Analytics 98

Predictive Analytics Data Modelling Data Mining Data Requirement 98

Sisense

APRIL 10, 2020

People looking into data science languages are usually confused about which language they should learn first: R or Python. Python’s readable syntax makes it easy to learn and understand, since it can be read much like a human language. Programmers choose different libraries because they help do a particular task more efficiently.

Visualization 98

Visualization Artificial Intelligence Data Mining Logistics 98

Astera

MARCH 28, 2024

Establishing a data catalog is part of a broader data governance strategy, which includes: creating a business glossary, increasing data literacy across the company and data classification. On the other hand, a data dictionary typically provides technical metadata and is commonly used as a reference for data modeling and database design.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Astera

MAY 14, 2024

As a result, your data becomes quick to discover, easier to understand, and more accessible by humans and machines. Examples include actions (such as data cleaning steps), tools used, tests performed, and lineage (data source). Examples include backup location, migration history (format changes), and digital signatures. Types of metadata.

Government 52

Government Data Governance Master Data Management Documentation 52

Whizlabs

APRIL 7, 2021

Learning these become extremely useful, which is why Whizlabs has introduced an online course: Introduction to Data Science with Python which will help the most non-tech savvy students to master Data science. Whizlabs made it a point to take the recommendations and dig deeper into the subject whilst coming out with a well modeled course.

Logistics 52

Logistics Data Mining Big Data Healthcare 52

Astera

JUNE 14, 2023

Automated Document Data Extraction Technologies Automated document data extraction pulls required information from different documents, typically leveraging technologies such as artificial intelligence (AI) and machine learning (ML). ICR converts handwritten characters into machine-readable text with high accuracy.

Documentation 52

Documentation Supply Chain Healthcare Logistics 52

Astera

OCTOBER 19, 2023

These user-friendly tools collect, clean, transform, and organize raw and incomplete data into a suitable and consistent format for further data processing, modeling, and analysis tasks. Data analysis demands precision, and at its core lies the vital role of data preparation tools. million as a result of data breaches. This was up 2.6%

IBM Support 40

IBM Support Data Quality IBM Maintenance Real-time Data 40

Sisense

JANUARY 22, 2021

A well-structured fintech algorithm could easily use machine learning (ML) to advise a human agent to approve or reject a business loan application. That advice is a quintessential actionable insight: The algorithm models the applicant’s probability of success by training on a mountain of historical data and market factors.

E-Commerce 52

E-Commerce Embedded Analytics Portfolio Management Healthcare 52

Astera

MAY 4, 2023

For example, the healthcare industry is subject to the Health Insurance Portability and Accountability Act (HIPAA), which ensure s privacy and security of personal health information. This incident is just a small example that highlights that ensuring transparency is not always an easy task.

Documentation 40

Documentation Artificial Intelligence Data Security Monitoring 40

Astera

FEBRUARY 1, 2024

Data modeling is the process of structuring and organizing data so that it’s readable by machines and actionable for organizations. In this article, we’ll explore the concept of data modeling, including its importance, types , and best practices. What is a Data Model? What is Data Modeling ?

Data Modelling 40

Data Modelling Retail Documentation Visualization 40

Marutitech

JANUARY 21, 2022

What is the CRISP-DM Process Model? A growing number of data science projects has led to an increase in the demand for data science managers. It is natural to think that any project manager can do the job or that a good senior data scientist will make an excellent data science manager. But this is not necessarily true. Engage stakeholders.

Project Management 113

Project Management Data Mining Data Analytics Data Analytics 113

Tableau

FEBRUARY 24, 2021

Editor's note: This article originally appeared in the Tableau Engineering Blog. Data science has exploded over the past decade, changing the way that we conduct business and prepare the next generation of young people for the jobs of the future. What is data science? It turns out data science is different things to different people.

Visualization 97

Visualization Data Visualization Data Discovery Customer Experience 97

Tableau

FEBRUARY 24, 2021

Editor's note: This article originally appeared in the Tableau Engineering Blog. Data science has exploded over the past decade, changing the way that we conduct business and prepare the next generation of young people for the jobs of the future. What is data science? It turns out data science is different things to different people.

Visualization 52

Visualization Data Visualization Data Discovery Customer Experience 52

Smart Data Collective

AUGUST 29, 2022

It can be even more valuable when used in conjunction with machine learning. Machine Learning Helps Companies Get More Value Out of Analytics. You will get even more value out of analytics if you leverage machine learning at the same time. This is why businesses are looking to leverage machine learning (ML).

Predictive Analytics 290

Predictive Analytics Banking Healthcare Retail 290

Data Pine

MAY 17, 2021

Businesses can benefit from improved data driven decision making as well as enhanced business processes and models and share insights across departments more fluently while propelling intelligent business strategies. What are the tools used for such a task? Table of Contents. 1) What Is Data Discovery? So, what is data discovery?

Data Discovery 64

Data Discovery Data Visualization Visualization Business Intelligence 64

Insight Software

JULY 17, 2023

To improve the effectiveness of the data cleaning process, the current trend is to migrate from manual data cleaning to more intelligent, machine learning-based processes. Finally, you can use classification or regression models to predict missing values. For example, higher income people may not disclose their incomes.

IBM Maintenance 52

IBM Maintenance IBM Support Predictive Analytics Embedded Analytics 52