CIO Business Intelligence

MAY 8, 2024

AI-powered data integration One of the most promising advancements in data integration is the integration of artificial intelligence (AI) and machine learning (ML) technologies. AI-powered data integration tools leverage advanced algorithms and predictive analytics to automate and streamline the data integration process.

Data Integration 69

Data Integration IoT Cost-Benefit Data Quality 69

Jedox

FEBRUARY 13, 2020

In the Digital Age, data-based decisions are becoming increasingly important for business. For controlling, this means using predictive analytics to produce more forward-looking analyses and increasingly decision-relevant forecasts instead of focusing on past tense reports. Automated sales forecast at Mitsui.

Forecasting 58

Forecasting Predictive Analytics Sales Data Integration 58

Smart Data Collective

OCTOBER 13, 2021

Data Virtualization can include web process automation tools and semantic tools that help easily and reliably extract information from the web, and combine it with corporate information, to produce immediate results. How does Data Virtualization manage data quality requirements? In forecasting future events.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

CIO Business Intelligence

JUNE 1, 2022

The company is applying winning insights from rapid, data-driven, evolutionary models versus relying on engine speed and aerodynamics alone to win races. Cloud-connected cars are now commonplace in the mainstream connected car market that is forecast to surpass $166 billion by 2025. The data transmitted from each car during a race ?

Manufacturing 94

Manufacturing Digital Transformation Predictive Analytics Strategy 94

datapine

JANUARY 21, 2020

Operational optimization and forecasting. Business intelligence and reporting are not just focused on the tracking part, but include forecasting based on predictive analytics and artificial intelligence that can easily help avoid making a costly and time-consuming business decision. Enhanced data quality.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

datapine

AUGUST 29, 2022

Reading this publication from our list of books for big data will give you the toolkit you need to make sure the former happens and not the latter. 7) Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel. An excerpt from a rave review: “The Freakonomics of big data.”.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. Our Top Data Science Tools.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Jedox

MARCH 7, 2023

The team needed detailed forecasts that could drill down to different product lines, SKUs, customers, materials, and regions. Mitsui piloted the Jedox predictive forecasting module, which supports a rolling annual sales forecast with AI-generated predictions.

Forecasting 52

Forecasting Sales Finance Reporting 52

IBM Big Data Hub

DECEMBER 7, 2023

Slice-and-dice analysis : OLAP allows users to slice and dice data along various dimensions, isolating specific segments for in-depth analysis. Improved decision-making Strategic planning and forecasting : OLAP helps businesses identify trends, patterns and potential risks, enabling better strategic planning and forecasting.

OLAP 59

OLAP Slice and Dice Cost-Benefit Data Warehouse 59

datapine

DECEMBER 4, 2019

Predictive & Prescriptive Analytics. Predictive Analytics: What could happen? We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. Graph Analytics.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Cloudera

SEPTEMBER 7, 2023

The way to manage this is by embedding data integration, data quality-monitoring, and other capabilities into the data platform itself , allowing financial firms to streamline these processes, and freeing them to focus on operationalizing AI solutions while promoting access to data, maintaining data quality, and ensuring compliance.

Insurance 81

Insurance Risk Data-driven Finance 81

CIO Business Intelligence

FEBRUARY 16, 2023

The defensive side includes traditional elements of data management, such as data governance and data quality. That is the domain of AI and advanced analytics that serve a role beyond just insight and business optimization. Analytics, Artificial Intelligence, Data Management, Predictive Analytics

Unstructured Data 98

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 98

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. QuickSight offers scalable, serverless visualization capabilities.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

FineReport

JULY 18, 2022

It is designed for both no-coding domain experts and experienced data scientists in an enterprise, regardless of their skill level. Key features: RapidMiner covers nearly all the functions in a unified data science lifecycle, from initial data preparation to advanced predictive analytics. SAS Forecasting.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

Alation

JANUARY 27, 2022

Raw data includes market research, sales data, customer transactions, and more. Analytics can identify patterns that depict risks, opportunities, and trends. And historical data can be used to inform predictive analytic models, which forecast the future. What Is the Value of Analytics?

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

Alation

MARCH 21, 2023

As an industry with tight margins, travel and tourism companies can use analytics to detect trends that help them reduce costs, decide future product and service offerings, and develop successful business strategies.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

CIO Business Intelligence

JUNE 14, 2023

Microsoft Certified Azure Data Scientist Associate The Microsoft Certified Azure Data Scientist Associate credential is a measure of a candidate’s ability to define and prepare Azure development environments, prepare data for modeling, perform feature engineering, and develop models. The credential does not expire.

Big Data 121

Big Data Data Analytics Analytics Predictive Modeling 121

FineReport

APRIL 26, 2023

.” This type of Analytics includes traditional query and reporting settings with scorecards and dashboards. Predictive Analytics assesses the probability of a specific occurrence in the future, such as early warning systems, fraud detection, preventative maintenance applications, and forecasting.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

FineReport

MARCH 24, 2024

Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue. Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

Jet Global

JULY 17, 2023

One of the major challenges in most business intelligence (BI) projects is data quality (or lack thereof). In fact, most project teams spend 60 to 80 percent of total project time cleaning their data—and this goes for both BI and predictive analytics.

Predictive Analytics 52

Predictive Analytics Reporting Software Strategy 52

DataKitchen

DECEMBER 9, 2022

In addition to monitoring the performance of data-related systems, DataOps observability also involves the use of analytics and machine learning to gain insights into the behavior and trends of data. By using DataOps, organizations can improve. Query> When do DataOps?

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

Smarten

NOVEMBER 3, 2017

These tools should include: Self-Serve Data Preparation – Allows business users to perform Advanced Data Discovery and auto-suggests relationships, reveals the impact and importance of key factors, recommends data type casts, data quality improvements and more!

Analytics 40

Analytics Visualization Experimentation Cost-Benefit 40

Andrew White

JANUARY 11, 2021

On end user clients calls, are you hearing a greater focus on use cases and greater need for prescriptive analytics, ex marketing analytics, sales analytics, healthcare, etc. where performance and data quality is imperative? Yes, prescriptive and predictive analytics remain very popular with clients.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52