CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. Decision intelligence seeks to update and reinvent decision support systems with a sophisticated mix of tools including artificial intelligence (AI) and machine learning (ML) to help automate decision-making.

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IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

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Cloudera

AUGUST 25, 2020

Thank you for joining us for part two of our discussion around data, analytics and machine learning within the Financial Service Sector Dr. Harmon. Machine Learning and AI provide powerful predictive engines that rely on historical data to fit the models. You can catch-up and read part 1 of the series, here.

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Prescriptive Analytics Technology Machine Learning Risk 74

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Data Science Data Analytics Prescriptive Analytics Analytics 76

Cloudera

JULY 18, 2018

As such, we are witnessing a revolution in the healthcare industry, in which there is now an opportunity to employ a new model of improved, personalized, evidence and data-driven clinical care. Together in tandem with MetiStream, a healthcare analytics software company, Cloudera addresses many of these challenges.

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Smart Data Collective

OCTOBER 14, 2019

From artificial intelligence and machine learning to blockchains and data analytics, big data is everywhere. Apache Hadoop develops open-source software and lets developers process large amounts of data across different computers by using simple models. Machine Learning. Big Data Skillsets.

Big Data 99

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Domino Data Lab

JUNE 2, 2019

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

Smart Data Collective

NOVEMBER 24, 2020

Prescriptive Analytics. Features: self-service visualizations and analysis machine-guided analysis associate model for exploring complex data integration of data from different sources data storytelling secure sharing of data models. This shows why self-service BI is on the rise. QlickSense.

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CIO Business Intelligence

FEBRUARY 16, 2023

All they would have to do is just build their model and run with it,” he says. 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 The company’s Findability.ai

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Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Access to Flexible, Intuitive Predictive Modeling. Analyze the Model with Visualization and Interpretation.

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Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 69

FineReport

JULY 28, 2021

Data science generally refers to all the knowledge, techniques, and methods used for data analysis, while data analytics is the manner of analyzing massive data. There are four primary types of data analytics: descriptive, diagnostic, predictive, and prescriptive analytics. . Insurance Dashboard (by FineReport).

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

Sisense

JUNE 30, 2020

When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations. Analytics acts as the source for data visualization and contributes to the health of any organization by identifying underlying models and patterns and predicting needs.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Cloudera

MARCH 2, 2018

Banking, transportation, healthcare, retail, and real estate, all have seen the emergence of new business models fundamentally changing how customers use their services. In the nonprofit sector, early applications of data analytics and machine learning have mostly focused on improving fundraising and marketing.

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AWS Big Data

MARCH 26, 2024

This can be achieved using AWS Entity Resolution , which enables using rules and machine learning (ML) techniques to match records and resolve identities. Unified customer profile Graph databases excel in modeling customer interactions and relationships, offering a comprehensive view of the customer journey.

Data Strategy 100

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Smarten

APRIL 10, 2023

Leverage Enterprise Investments for Predictive Analytics and Gain Numerous Advantages! Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Why the focus on predictive analytics? It’s simple!

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Predictive Analytics Predictive Modeling Analytics Prescriptive Analytics 52

BizAcuity

MARCH 31, 2022

The aim of predictive analytics is, as the name suggests, to predict and forecast outcomes. For accurate predictions, companies now use various data models, machine and deep learning techniques to continuously improve and refine the quality of the outcome. AI Services.

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DataRobot Blog

MARCH 15, 2022

In addition, as more decisions are guided by machine learning, there’s the prerequisite to monitor, assess, and explain AI model performance against the constant of changing data (volumes fluctuate, casemix varies, clinical system configuration changes, and so on).

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FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue.

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Alation

MARCH 21, 2023

They may also suffer from data duplication, which undermines their analytics models. How is data analytics used in the travel industry? To support documentation, Finnair leverages Alation’s artificial intelligence (AI) and machine learning (ML) metadata recommendations to ensure data quality.

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Data Analytics Analytics Data-driven Big Data 52

FineReport

APRIL 26, 2023

For example, a computer manufacturing company could develop new models or add features to products that are in high demand. Predictive Analytics assesses the probability of a specific occurrence in the future, such as early warning systems, fraud detection, preventative maintenance applications, and forecasting. Easy implementation.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

datapine

NOVEMBER 27, 2019

Often seen as the highest foe-friend of the human race in movies ( Skynet in Terminator, The Machines of Matrix or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite the legit warnings of some reputed scientists and tech-entrepreneurs. 4) Predictive And Prescriptive Analytics Tools.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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. The commercial use of predictive analytics is a relatively new thing.

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Rocket-Powered Data Science

OCTOBER 6, 2023

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. How do predictive and prescriptive analytics fit into this statistical framework?

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Business Analytics Prescriptive Analytics Analytics Statistics 157

Andrew White

JANUARY 11, 2021

Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. The work of data science is more tied to machine learning and so AI and those projects do not focus only on analysis but also automation. Try some gamification?

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Data Analytics Analytics Data-driven Finance 52

Smarten

SEPTEMBER 9, 2024

‘To fulfill the role of a Citizen Data Scientist, business users today can leverage augmented analytics solutions; that is analytics that provide simple recommendations and suggestions to help users easily choose visualization and predictive analytics techniques from within the analytical tool without the need for expert analytical skills.’

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Alation

AUGUST 26, 2021

For this reason, data intelligence software has increasingly leveraged artificial intelligence and machine learning (AI and ML) to automate curation activities, which deliver trustworthy data to those who need it. Artificial Intelligence and Machine Learning (AI & ML) are forward-looking. Augmented Analytics.

Metadata 64

Metadata Data Governance Dashboards Software 64

Smarten

APRIL 11, 2018

Gartner defines a Citizen Data Scientist as ‘a person who creates or generates models that leverage predictive or prescriptive analytics but whose primary job function is outside of the field of statistics and analytics.’ The Analytics Translator is an important member of the new analytical team.

Analytics 40

Analytics Prescriptive Analytics Business Intelligence ROI 40

Smarten

SEPTEMBER 9, 2024

Gartner defines a citizen data scientist as, ‘ a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.’ So, let’s get started. What is a Cititzen Data Scientist? Who is a Citizen Data Scientist?

Consulting 52

Consulting Cost-Benefit Data Science Business Intelligence 52

Jet Global

MAY 1, 2023

These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Pricing model: The pricing scale is dependent on several factors. These advanced analytics become easy for users to apply in their own analyses.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Smarten

MARCH 20, 2025

In 2016, the technology research firm, Gartner, coined the term Citizen Data Scientist, and defined it as a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.

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