CIO Business Intelligence

FEBRUARY 20, 2025

This is due, on the one hand, to the uncertainty associated with handling confidential, sensitive data and, on the other hand, to a number of structural problems. Most use master data to make daily processes more efficient and to optimize the use of existing resources. Kastrati: The labor market will change even more than it does today.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

CIO Business Intelligence

OCTOBER 4, 2022

As they put it, “Such co-inventions include machine learning applications and predictive analytics embedded across the organization in various business processes, which increase the value of work conducted by data users and decision-makers.”. We agree and can bring some additional perspective on the upside of that kind of approach.

Machine Learning 118

Machine Learning Data Architecture Uncertainty Data-driven 118

CIO Business Intelligence

MARCH 14, 2022

Hubbard defines measurement as: “A quantitatively expressed reduction of uncertainty based on one or more observations.”. This acknowledges that the purpose of measurement is to reduce uncertainty. And the purpose of reducing uncertainty is to make better decisions. Data creates the context for decision-making.

Uncertainty 105

Uncertainty Measurement Cost-Benefit Optimization 105

CIO Business Intelligence

SEPTEMBER 2, 2022

How do you deal with uncertainties and where do you see technologies like AI or ML helping out in this respect? Khare: I look at uncertainty at two tiers. One is macro-level uncertainties, and the second is micro-level. The pandemic falls into the macro-level because we really can’t predict those kinds of events.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

CIO Business Intelligence

SEPTEMBER 2, 2022

How do you deal with uncertainties and where do you see technologies like AI or ML helping out in this respect? Khare: I look at uncertainty at two tiers. One is macro-level uncertainties, and the second is micro-level. The pandemic falls into the macro-level because we really can’t predict those kinds of events.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

Smart Data Collective

AUGUST 18, 2021

Predictive analytics, in contrast, goes further than keyword scanning software by highlighting a plethora of valuable metrics like experience, job titles, qualifications, skills, industries, and businesses, and compares these to the open job description and even existing employee data. Finding the best fit for an open position.

Data Science 139

Data Science Management Big Data Metrics 139

CIO Business Intelligence

AUGUST 30, 2022

Predictive analytics help to anticipate consumption patterns, while a combination of predictive demand modeling and real time assessment provides clear visibility into the supply chain – enabling actions to be taken such as rerouting, reprioritization of production/shipping schedules and changes in inventory levels.

Uncertainty 98

Uncertainty Manufacturing Predictive Analytics Modeling 98

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another. TIBCO Spotfire.

Data mining 144

Data mining Data-driven Statistics OLAP 144

CIO Business Intelligence

JUNE 7, 2024

But with the addition of more renewable energy to its portfolio, weather uncertainty becomes a greater challenge for AES. The project, dubbed Farseer AI Generation Forecasting and Market Automation Program, was developed by a handful of AES data scientists in partnership with Google.

IT 128

IT Forecasting Machine Learning Modeling 128

Sisense

SEPTEMBER 9, 2019

We knew our journey with predictive analytics and sentiment analysis was going to be a gradual progression that would eventually help us understand and better serve our customers. Then we ran Kraken’s machine learning and predictive modeling engine to get the results.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Data-driven Forecasting 75

Jedox

OCTOBER 8, 2020

We are currently operating in an environment with a very high (if not the highest ever) level of VUCA, (Volatility, Uncertainty, Complexity, Ambiguity). The way you mitigate uncertainty is with planning, planning, and more planning. To quote General/President Dwight D.

Uncertainty 75

Uncertainty Cost-Benefit Unstructured Data Data-driven 75

Smart Data Collective

MARCH 21, 2022

In the early days, organizations used a central data warehouse to drive their data analytics. Even today, there are a large number of them using data lakes to drive predictive analytics. In a centralized ecosystem, everyone is dependent upon everyone else thereby creating uncertainties and interrupted flow of accurate data.

Management 75

Management Data Lake Uncertainty Data Warehouse 75

Sisense

JULY 6, 2020

Analytics are essential in a crisis. Uncertainty often surfaces new opportunities as business leaders are forced to consider changes around key parts of the business. Organizations are leaning on data and insights to navigate a new path forward as they deal with the crisis, but also as they reset their businesses.

Data-driven 81

Data-driven Uncertainty Reporting Predictive Analytics 81

bridgei2i

JULY 8, 2020

This is probably the first time ever that we are witnessing a demand, a supply, and also a resource uncertainty. Vignesh: Ganesh, you really highlighted some very important themes. These are strange times. And all at the same time. So, what do I mean by this? So, let’s say you are a CXO in a retail or consumer goods barring essentials.

Digital Transformation 132

Digital Transformation Enterprise Insurance Risk 132

Sisense

OCTOBER 6, 2020

These techniques allow you to: See trends and relationships among factors so you can identify operational areas that can be optimized Compare your data against hypotheses and assumptions to show how decisions might affect your organization Anticipate risk and uncertainty via mathematically modeling.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Jet Global

NOVEMBER 8, 2021

As Deloitte notes in its Finance 2025 Revisited report: “Automation gains… generally helped a remote workforce keep the lights on, not produce predictive analytics (though that capability readily exists).” If your organization is poised for finance transformation in 2022, insightsoftware can help.

Finance 52

Finance Predictive Analytics Reporting Uncertainty 52

Jet Global

APRIL 9, 2023

Predictive Finally, predictive data analysis and forecasting is the capstone to true data fluency, representing true synergy of people, data, and tools. With all the other, more foundational, challenges to work through, predictive analytics unsurprisingly scored lowest on the list of current capabilities.

Finance 52

Finance Forecasting Predictive Analytics Data-driven 52

CIO Business Intelligence

MARCH 30, 2022

Disruption and uncertainties will keep going for the following years, and being agile and resilient needs to become part of t the manufacturer’s DNA. What is paramount here is agility and resiliency,” Ory said. It’s these two elements that are driving opportunity of optimisation and additional profit for our customers.”. Industry 4.0

Manufacturing 52

Manufacturing Uncertainty Digital Transformation Predictive Analytics 52

Domino Data Lab

JUNE 2, 2019

Clearly, when we work with data and machine learning, we’re swimming in those waters of decision-making under uncertainty. I recall a “Data Drinkup Group” gathering at a pub in Palo Alto, circa 2012, where I overheard Pete Skomoroch talking with other data scientists about Kahneman’s work.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

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. Identify those most at risk or most affected by a problem more accurately by using predictive analytics.

Data-driven 43

Data-driven Prescriptive Analytics Machine Learning Descriptive Analytics 43

Domino Data Lab

JULY 22, 2019

You know, case in point, if you were to talk about predictive analytics 20 years ago, the main people in the field would have laughed you out of the room. Predictive analytics, yeah, not so much.” They learned about a lot of process that requires that you get rid of uncertainty. How could that make sense?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Smart Data Collective

FEBRUARY 14, 2023

One of the biggest is that more financial institutions are using predictive analytics tools to assist with asset management. Predictive Asset Analytics, Riskalyze and Altruist are some of the tools that use predictive analytics to improve asset management for both individual and institutional investors.

Predictive Analytics 132

Predictive Analytics Management Analytics Uncertainty 132

Smarten

JULY 18, 2022

By incorporating analytics into day-to-day activities and allowing access for business users, the business can encourage the transition from business user to Citizen Data Scientist and create a comprehensive system of analytics with governance and collaboration to ensure security, appropriate access, mobile use and fact-based decision-making.

Uncertainty 52

Uncertainty Predictive Analytics Forecasting Analytics 52

Jet Global

NOVEMBER 7, 2023

If any one word could encapsulate 2023, it would be “uncertainty.” For most of the year, finance teams have been preparing for a recession that never quite reached the heights (or depths) heralded by the media.

Finance 52

Finance Uncertainty Reporting Forecasting 52