Marktechpost

MAY 12, 2024

The technology provides automated, improved machine-learning techniques for fraud identification and proactive enforcement to reduce fraud and block rates. Fynt AI Fynt AI is an AI automation solution developed primarily for corporate finance departments. It is based on adjustable and explainable AI technology.

AI Tools 105

AI Tools Neural Network Artificial Intelligence Artificial Intelligence 105

IBM Journey to AI blog

OCTOBER 20, 2023

AI technology is quickly proving to be a critical component of business intelligence within organizations across industries. AI platforms offer a wide range of capabilities that can help organizations streamline operations, make data-driven decisions, deploy AI applications effectively and achieve competitive advantages.

Machine Learning 242

Machine Learning Automation AI AI 242

Pickl AI

JULY 3, 2023

What is Business Intelligence? Business Intelligence (BI) refers to the technology, techniques, and practises that are used to gather, evaluate, and present information about an organisation in order to assist decision-making and generate effective administrative action. billion in 2015 and reached around $26.50

Business Intelligence 52

Business Intelligence ETL Continuous Learning Data Integration 52

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality 130

Data Quality Metadata ETL Big Data 130

Marktechpost

JULY 18, 2023

The entire ETL procedure is automated using an ETL tool. ETL solutions employ several data management strategies to automate the extraction, transformation, and loading (ETL) process, reducing errors and speeding up data integration. Informatica created the PowerCenter product as a means of integrating data.

ETL 52

ETL Data Integration Business Intelligence Automation 52

Attivio

JUNE 8, 2015

Featuring self-service data discovery acceleration capabilities, this new solution solves a major issue for business intelligence professionals: significantly reducing the tremendous amount of time being spent on data before it can be analyzed.

Business Intelligence 40

Business Intelligence Big Data Data Discovery Data Scientist 40

Marktechpost

JUNE 5, 2024

Analytics, management, and business intelligence (BI) procedures, such as data cleansing, transformation, and decision-making, rely on data profiling. Content and quality reviews are becoming more important as data sets grow in size and variety of sources. The 18 best data profiling tools are listed below.

Data Quality 115

Data Quality Metadata Data Integration ETL 115

Pickl AI

NOVEMBER 18, 2024

Selecting the right alternative ensures efficient data-driven decision-making and aligns with your organisation’s goals and budget. Introduction Power BI has become one of the most popular business intelligence (BI) tools, offering powerful Data Visualisation, reporting, and decision-making features. billion to USD 54.27

Data Analysis 52

Data Analysis Business Intelligence Big Data Artificial Intelligence 52

ODSC - Open Data Science

SEPTEMBER 27, 2023

Storage Optimization: Data warehouses use columnar storage formats and indexing to enhance query performance and data compression. They excel at managing structured data and supporting ACID (Atomicity, Consistency, Isolation, Durability) transactions.

Big Data 98

Big Data Metadata ETL Business Intelligence 98

IBM Journey to AI blog

DECEMBER 16, 2022

After all, Alex may not be aware of all the data available to her. With a data catalog, Alex can discover data assets she may have never found otherwise. Meaningful business context. Instead, governance rules automate which data is viewable and accessible based on permissions and policies.

Metadata 130

Metadata Data Quality Data Discovery Data Scientist 130

Pickl AI

SEPTEMBER 5, 2024

Summary: Operations Analysts play a crucial role in enhancing organisational efficiency by analysing processes, implementing improvements, and leveraging data-driven insights. In 2024, they face emerging trends such as automation and agile methodologies, requiring a diverse skill set. What Tools Do Operations Analysts Commonly Use?

Data Analysis 52

Data Analysis Data Quality Automation Solutions Analyst 52

Pickl AI

OCTOBER 16, 2024

Summary: Relational Database Management Systems (RDBMS) are the backbone of structured data management, organising information in tables and ensuring data integrity. Introduction RDBMS is the foundation for structured data management. Introduction RDBMS is the foundation for structured data management.

Data Integration 52

Data Integration Big Data Business Intelligence Machine Learning 52

AWS Machine Learning Blog

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. In this post, we discuss how to address these challenges holistically.

Generative AI 121

Generative AI Data Ingestion AI AI 121

Pickl AI

SEPTEMBER 11, 2024

This layer includes tools and frameworks for data processing, such as Apache Hadoop, Apache Spark, and data integration tools. Data as a Service (DaaS) DaaS allows organisations to access and integrate data from various sources without the need for complex data management.

Big Data 52

Big Data Data Integration Machine Learning Data Ingestion 52

IBM Journey to AI blog

OCTOBER 12, 2023

Security and privacy —When all data scientists and AI models are given access to data through a single point of entry, data integrity and security are improved. They can also spot and root out bias and drift proactively by monitoring, cataloging and governing their models.

Data Scientist 253

Data Scientist Metadata Responsible AI Explainability 253

IBM Journey to AI blog

SEPTEMBER 17, 2024

Its in-memory processing helps to ensure that data is ready for quick analysis and reporting, enabling real-time what-if scenarios and reports without lag. Our solution handles massive multidimensional cubes seamlessly, enabling you to maintain a complete view of your data without sacrificing performance or data integrity.

Big Data 100

Big Data Metadata Business Intelligence Data Integration 100

Marktechpost

JULY 23, 2023

A data warehouse is a data management system for data reporting, analysis, and storage. It is an enterprise data warehouse and is part of business intelligence. Data from one or more diverse sources is stored in data warehouses, which are central repositories.

Machine Learning 52

Machine Learning ETL Big Data Data Integration 52

AWS Machine Learning Blog

SEPTEMBER 6, 2023

Realizing the impact of these applications can provide enhanced insights to the customers and positively impact the performance efficiency in the organization, with easy information retrieval and automating certain time-consuming tasks. We encourage you to deploy the AWS CDK app into your account and build the Generative AI solution.

Generative AI 122

Generative AI Large Language Models AI AI 122

Pickl AI

JUNE 6, 2024

Correction Power Once errors are identified, data scrubbing doesn’t just point and laugh (well, metaphorically). This can involve manual intervention by data analysts for complex issues. Data scrubbing is the knight in shining armour for BI. Data scrubbing helps organizations comply with data privacy regulations.

Machine Learning 40

Machine Learning Algorithm Business Intelligence Data Quality 40

AWS Machine Learning Blog

NOVEMBER 15, 2023

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

Data Ingestion 126

Data Ingestion Metadata NLP Data Scientist 126

ODSC - Open Data Science

JANUARY 30, 2024

Not only does it involve the process of collecting, storing, and processing data so that it can be used for analysis and decision-making, but these professionals are responsible for building and maintaining the infrastructure that makes this possible; and so much more.

Data Science 52

Data Science Data Mining Data Scientist Machine Learning 52

Marktechpost

JULY 17, 2023

Data gathering, pre-processing, modeling, and deployment are all steps in the iterative process of predictive analytics that results in output. We can automate the procedure to deliver forecasts based on new data continuously fed throughout time. This tool’s user-friendly UI consistently receives acclaim from users.

Data Mining 98

Data Mining Machine Learning Data Scientist Artificial Intelligence 98

AWS Machine Learning Blog

OCTOBER 21, 2024

Automating this will help to save time and effort. As an Information Technology Leader, Jay specializes in artificial intelligence, generative AI, data integration, business intelligence, and user interface domains. Currently, the model weights need to be all-inclusive, including the adapter weights.

Generative AI 139

Generative AI ML Python AI 139

Artificial Corner

JUNE 6, 2023

This period also saw the development of the first data warehouses, large storage repositories that held data from different sources in a consistent format. The concept of data warehousing was introduced by Bill Inmon, often referred to as the “father of data warehousing.” This avoids data lock-in from proprietary formats.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

The MLOps Blog

MAY 17, 2023

Significance of ETL pipeline in machine learning The significance of ETL pipelines lies in the fact that they enable organizations to derive valuable insights from large and complex data sets. Here are some specific reasons why they are important: Data Integration: Organizations can integrate data from various sources using ETL pipelines.

ETL 59

ETL ML Machine Learning Data Scientist 59

Marktechpost

NOVEMBER 1, 2024

Leveraging Google’s expertise in data handling and AI innovation, this platform offers extensive analytics capabilities that range from marketing and business intelligence to data science. Google Cloud Smart Analytics supports organizations in building data-driven workflows and implementing AI at scale.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence AI Tools Machine Learning 98

Unite.AI

NOVEMBER 13, 2024

By integrating AI directly into platforms like Excel and Google Sheets, LLMs enhance spreadsheets with natural language capabilities that simplify complex tasks. Users can now perform complex data analysis, automate workflows, and generate insights by simply typing a request in plain language.

Large Language Models 147

Large Language Models Data Analysis AI AI 147

Marktechpost

NOVEMBER 4, 2024

In order to solve particular business questions, this process usually includes developing and managing data systems, collecting and cleaning data, analyzing it statistically, and interpreting the findings. Google Cloud Smart Analytics supports organizations in building data-driven workflows and implementing AI at scale.

Data Analysis 75

Data Analysis Machine Learning Data Science Python 75

IBM Journey to AI blog

AUGUST 4, 2023

Data mesh Another approach to data democratization uses a data mesh , a decentralized architecture that organizes data by a specific business domain. Then, it applies these insights to automate and orchestrate the data lifecycle. Read more: Data fabric versus data mesh: Which is right for you?

Machine Learning 189

Machine Learning Metadata AI AI 189