Dataversity

DECEMBER 16, 2022

Unsupervised and self-supervised learning are making ML more accessible by lowering the training data requirements. 2022 was a big year for AI, and we’ve seen significant advancements in various areas – including natural language processing (NLP), machine learning (ML), and deep learning.

Data Requirement 130

Data Requirement Artificial Intelligence 130

The BAWorld

DECEMBER 6, 2023

Consider pursuing certifications to validate your understanding of key data analysis tools and methodologies, enhancing your credibility among potential employers. Step 2: Obtaining essential skills Data analysts play a crucial role in extracting meaningful insights from data, requiring a blend of technical and analytical skills.

Data Analytics 52

Data Analytics Data Analytics Artificial Intelligence Visualization 52

Actian

SEPTEMBER 12, 2019

Artificial Intelligence (AI) systems seem to be everywhere and for a good reason. Artificial Intelligence is arguably the most important technological development of the modern era. You can learn more about Actian’s Cloud Data Warehouse here. AI represents the next generation of computing capabilities.

Data Requirement 8

Data Requirement Artificial Intelligence Data Warehouse Cloud Computing 8

Astera

MAY 4, 2023

Adopting AI for Advanced Business Intelligence and Analytics Artificial Intelligence offers a wide range of benefits that can significantly enhance the capabilities of BI and analytics.

Business Intelligence 40

Business Intelligence Business Intelligence Predictive Analytics Supply Chain 40

GAVS Technology

AUGUST 17, 2021

Artificial Intelligence and Machine Learning (AI/ML) are technologies that are starting to have a significant impact on humanity. With voice-enabled devices, ride-sharing apps, smart email suggestions, and more, AI and ML have significantly enhanced the quality of our lives.

Cybersecurity 40

Cybersecurity Healthcare Artificial Intelligence Government 40

Sisense

AUGUST 14, 2020

Artificial intelligence is transforming products in surprising and ingenious ways. In the case of a stock trading AI, for example, product managers are now aware that the data required for the AI algorithm must include human emotion training data for sentiment analysis.

Healthcare 98

Healthcare Cybersecurity Predictive Analytics Artificial Intelligence 98

Astera

JUNE 14, 2023

Limitations of Manual Document Data Extraction Besides being error-prone and time-consuming, manual document data extraction has several other challenges and limitations, including: Lack of Scalability: Manual methods are not scalable, making it challenging to handle increasing volumes of documents efficiently.

Documentation 52

Documentation Supply Chain Healthcare Logistics 52

Inflexion Analytics

APRIL 15, 2024

In the ever-evolving landscape of artificial intelligence and natural language processing, Large Language Models (LLMs) are capturing the spotlight for their incredible versatility and problem-solving capabilities. Data Efficiency: LLMs require relatively small amounts of domain-specific data to fine-tune.

Artificial Intelligence 52

Artificial Intelligence Documentation Digital Innovation 52

Inflexion Analytics

APRIL 15, 2024

In the ever-evolving landscape of artificial intelligence and natural language processing, Large Language Models (LLMs) are capturing the spotlight for their incredible versatility and problem-solving capabilities. Data Efficiency: LLMs require relatively small amounts of domain-specific data to fine-tune.

Artificial Intelligence 52

Artificial Intelligence Documentation Digital Innovation 52

Astera

AUGUST 15, 2023

Data Format Standardization: EDI relies on standardized data formats and protocols for seamless data exchange between different parties. Ensuring uniformity in data formats and protocols can be challenging when dealing with multiple stakeholders who may have varying systems and data requirements.

Finance 52

Finance Data Security Customer Experience Customer Experience 52

Astera

MAY 11, 2023

The Power of Synergy: AI and Data Extraction Transforming Business Intelligence The technologies of AI and Data Extraction work in tandem to revolutionize the field of Business Intelligence. AI can analyze vast amounts of data but needs high-quality data to be effective.

Business Intelligence 40

Business Intelligence Business Intelligence Supply Chain Logistics 40

Astera

MAY 9, 2023

Choosing the Right Data Integration Solution As the explosion in data volume continues, traditional methods of data management and integration cannot be used anymore. While AI-based data integration is now the talk of the town, it’s important to choose the right solution to handle modern data requirements.

Healthcare 40

Healthcare Retail Finance Data Quality 40

Marutitech

APRIL 7, 2022

This is where data cleaning comes in. . Data cleaning involves removing redundant and duplicate data from our data sets, making them more usable and efficient. . Converting data requires some data manipulation and preparation, allowing you to uncover valuable insights and make critical business decisions.

Predictive Analytics 98

Predictive Analytics Data Modelling Data Mining Data Requirement 98

Astera

MAY 6, 2024

It utilizes artificial intelligence to analyze and understand textual data. To assist users in navigating this choice, the following guide outlines the essential considerations for choosing a data mining tool that aligns with their specific needs: 1. Cons: There’s a high learning curve for using Apache Mahout.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Astera

MAY 26, 2023

Similarly, other departments like Supply Chain need invoices to update their own inventory records. Automated Invoice Data Extractio n is a process that uses either logical templates or Artificial Intelligence (AI) to automatically extract data from invoices, including purchase order numbers, vendor information, and payment terms.

Retail 40

Retail Supply Chain Finance Data Quality 40

Marutitech

OCTOBER 8, 2021

You can creatively use advanced artificial intelligence and machine learning tools for doing research and draw out the analysis. Since tagging data requires consistency for accurate results, a good definition of the problem is a must. In this case, determining the neutral tag is the most critical and challenging problem.

Monitoring 98

Monitoring Documentation Logistics Customer Experience 98

Astera

SEPTEMBER 20, 2023

Data Extraction Once you have your data sources in mind, you’ll need to devise an efficient data extraction plan to pull data from each source. Modern organizations use advanced data extraction tools to access and retrieve relevant information.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Astera

SEPTEMBER 20, 2023

Data Extraction Once you have your data sources in mind, you’ll need to devise an efficient data extraction plan to pull data from each source. Modern organizations use advanced data extraction tools to access and retrieve relevant information.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data E-Commerce 52

Marutitech

DECEMBER 17, 2021

Manual forecasting of data requires hours of labor work with highly professional analysts to draw out accurate outputs. This predictive analytics algorithm was initially developed by Facebook and is used internally by the company for forecasting. Most Popular Predictive Analytics Techniques .

Predictive Analytics 140

Predictive Analytics Data Mining Finance Data Analytics 140

The BAWorld

NOVEMBER 22, 2021

Data Modeling. Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Metadata is the data about data; it gives information about the data. for accurate analysis.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Data Pine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 3) Artificial Intelligence.

Business Intelligence 144

Business Intelligence Business Intelligence Artificial Intelligence Data Discovery 144

Actian

JULY 31, 2019

First, many of them are based on inflexible architectures in terms of their capability to manage JSON and time-series data and the cost to expand them to administer larger datasets or complexity of modern analytics, such as Artificial Intelligence (AI) and Machine Learning (ML).

IBM Support 8

IBM Support Documentation IBM Maintenance Data Warehouse 8

Insight Software

MAY 1, 2023

Strategic Objective Create an engaging experience in which users can explore and interact with their data. Requirement Filtering Users can choose the data that is important to them and get more specific in their analysis. Drilling Users can dig deeper and gain greater insights into the underlying data.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52