CIO Business Intelligence

JULY 5, 2022

What is business analytics? Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. What are the benefits of business analytics? What is the difference between business analytics and data analytics?

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Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 118

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 77

Data Science Data Analytics Prescriptive Analytics Analytics 77

Smarten

AUGUST 8, 2017

A vast amount of data, classified and grouped, running analytics to predict what will be the next event that one or more elements of the group will take. Predictive analytics like this allows pushing of right products to e-commerce shoppers. Some data, like Government spending in the region, may or may not be available.

Predictive Analytics 65

Predictive Analytics Analytics Prescriptive Analytics Sales 65

CIO Business Intelligence

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. What are the four types of data analytics?

Data Analytics 122

Data Analytics Diagnostic Analytics Management Analytics 122

Birst BI

OCTOBER 30, 2018

Fortunately, advances in analytic technology have made the ability to see reliably into the future a reality. Today, the most common usage of business intelligence is for the production of descriptive analytics. . Descriptive Analytics: Valuable but limited insights into historical behavior.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Jedox

JANUARY 29, 2019

In today’s organizations, the role of financial controlling or FP&A is not only to provide financial insights so business partners can make better decisions, but it is also to lead the way towards a more mature use of analytics technology including predictive analytics for sales forecasting. Making AI Real (Part 2).

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Predictive Analytics Forecasting Sales Analytics 41

BizAcuity

MARCH 31, 2022

The widespread adoption of AI technology is fueled by 3 major challenges that businesses have been facing since the last decade. Combined, it has come to a point where data analytics is your safety net first, and business driver second. Artificial Intelligence Analytics. Fast shifting trends in consumer behavior.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Sisense

JUNE 30, 2020

Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. Data visualization and visual analytics are two terms that come up a lot when new and experienced analytics users alike delve into the world of data in their quest to make smarter decisions. Thomas, and Kristin A.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Jedox

JULY 31, 2018

We also took a first look at how fp&a and business intelligence professionals can start to derive tangible value from these technologies for Enterprise Performance Management. Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of data analytics from descriptive to prescriptive.

Technology 44

Technology Prescriptive Analytics Machine Learning Business Intelligence 44

BizAcuity

MARCH 8, 2019

Workforce Analytics – What is its need for companies. Workforce Analytics in simple terms can be defined as an advanced set of software and methodology tools that measures, characterizes, and organizes sophisticated employee data and these tools helps in understanding the employee performance in a logical way.

Analytics 73

Analytics Prescriptive Analytics Cost-Benefit Metrics 73

Smart Data Collective

OCTOBER 13, 2021

This is something that you can learn more about in just about any technology blog. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future. There is little use for data analytics without the right visualization tool. Prescriptive analytics.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Alation

MARCH 21, 2023

For example, airlines have historically applied analytics to revenue management, while successful hospitality leaders make data-driven decisions around property allocation and workforce management. Why is data analytics important for travel organizations? Today, modern travel and tourism thrive on data.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

CIO Business Intelligence

NOVEMBER 14, 2022

The concept of DSS grew out of research conducted at the Carnegie Institute of Technology in the 1950s and 1960s, but really took root in the enterprise in the 1980s in the form of executive information systems (EIS), group decision support systems (GDSS), and organizational decision support systems (ODSS). Crop planning. Clinical DSS.

Data mining 122

Data mining Data-driven Statistics OLAP 122

Sisense

AUGUST 11, 2019

This is where Business Analytics (BA) and Business Intelligence (BI) come in: both provide methods and tools for handling and making sense of the data at your disposal. BA and BI are broad terms covering all kinds of technologies and approaches – and, to add to the confusion, are often used interchangeably. What’s In a Name?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

FineReport

APRIL 26, 2023

In this article, we will explore the importance of Big Data, why enterprises need Big Data tools, how to choose the right Big Data analytics tools and provide a list of the top 10 Big Data analytics tools available today. Descriptive Analytics is used to determine “what happened and why.” What is Big Data?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

IBM Big Data Hub

JULY 27, 2022

Specifically, AIOps uses big data, analytics, and machine learning capabilities to do the following: Collect and aggregate the huge and ever-increasing volumes of operations data generated by multiple IT infrastructure components, applications and performance-monitoring tools. Predictive analytics to show what will happen next.

Prescriptive Analytics 93

Prescriptive Analytics Descriptive Analytics Data-driven Cost-Benefit 93

Jet Global

MAY 1, 2023

Introduction Why should I read the definitive guide to embedded analytics? But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

CIO Business Intelligence

FEBRUARY 16, 2023

Advances in imaging technology present Straumann Group with the opportunity to provide its customers with new capabilities to offer their clients. The next goal, with the aid of partner Findability Sciences, will be to build out ML and AI pipelines into an information delivery layer that can support predictive and prescriptive analytics. “As

Unstructured Data 97

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 97

Smarten

JUNE 2, 2017

From reporting to visualised dashboard to predictive analytics. We know that by designing self-learning programs, we are in a position to provide prescriptive analytics. Some prescriptive analytics based on known parameters were always a part of ERP or BI offering. This was early predictive or was it?

Business Intelligence 40

Business Intelligence Visualization Prescriptive Analytics Predictive Analytics 40

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios.

Statistics 52

Statistics Data mining Visualization Reporting 52

Cloudera

MARCH 2, 2018

The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models. Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques.

Data-driven 43

Data-driven Prescriptive Analytics Descriptive Analytics Machine Learning 43

Andrew White

JANUARY 11, 2021

It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. So the material is not designed for IT – but spans business and technology. The fill report is here: Leadership Vision for 2021: Data and Analytics. Governance.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. One ride-hailing transportation company uses big data analytics to predict supply and demand, so they can have drivers at the most popular locations in real time.

Machine Learning 55

Machine Learning Data Science Statistics Deep Learning 55

Sisense

SEPTEMBER 12, 2019

And every business – regardless of the industry, product, or service – should have a data analytics tool driving their business. Our go-to approach for analytics that feeds well into a BI strategy is the Evolution of Analytics chart (below). With that being said, it’s not enough to just have a tool. Find a bottleneck in R&D?

Strategy 81

Strategy Dashboards Diagnostic Analytics Prescriptive Analytics 81

Domino Data Lab

JUNE 2, 2019

And by “scale” I’m referring to what is arguably the largest, most successful data analytics operation in the cloud of any public firm that isn’t a cloud provider. Because of anxieties and misunderstandings around the HIPPO (highest paid person’s opinion), who may have little understanding about technology and use cases.

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Data-driven Data Science Machine Learning Modeling 110