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?

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BizAcuity

AUGUST 26, 2019

This is what makes the casino industry a great use case for prescriptive analytics technologies and applications. The need for prescriptive analytics. Prescriptive analytics is the area of business analytics (BA) dedicated to finding the best course of action for a given situation.

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CIO Business Intelligence

OCTOBER 4, 2023

Certified Information Systems Auditor (CISA); PMI Program, Portfolio, and Risk Management Professionals (PgMP, PfMP and PMI-RMP); Six Sigma Black Belt and Master Black Belt; Certified in Governance, Risk, and Compliance (ISC2); and Certified in Risk and Information Systems Control (CRISC) also drew large premiums.

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Smarten

JULY 30, 2024

Gartner predicted that, ‘75% of organizations will have deployed multiple data hubs to drive mission-critical data and analytics sharing and governance.’ A misstep in any of these areas can create risk, damage your business reputation, or put you years behind your competition. That’s why your business needs predictive analytics.

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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.

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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.’ Complete Set of Analytical Techniques. Predictive Analytics Using External Data. Competitive Changes.

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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. One of the key takeaways from recent times that should be considered into the future, is that banks need to rethink how they look at tail risk or extreme events that rarely happen. .

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Birst BI

OCTOBER 30, 2018

Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? Fortunately, advances in analytic technology have made the ability to see reliably into the future a reality.

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BizAcuity

FEBRUARY 21, 2025

Forecast trends and act strategically : Integration with advanced analytics and AI-powered insights helps businesses not only predict trends but also take proactive steps to stay ahead of competitors. Without the right expertise, companies risk misconfigurations or suboptimal integrations that dont deliver the desired results.

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BizAcuity

MARCH 31, 2022

Combined, it has come to a point where data analytics is your safety net first, and business driver second. By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. Artificial Intelligence Analytics. Uncertain economic conditions.

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Cloudera

JULY 18, 2018

Despite advances made in EHRs of late, they, unfortunately, do not provide advanced analytics or intelligent search for that matter. Together in tandem with MetiStream, a healthcare analytics software company, Cloudera addresses many of these challenges. Ember exploits FHIR beyond data exchange to empower interoperable analytics.

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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.

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AWS Big Data

MARCH 26, 2024

We structure it in five pillars that power C360: data collection, unification, analytics, activation, and data governance, along with a solution architecture that you can use for your implementation. AWS Data Exchange makes it straightforward to find, subscribe to, and use third-party data for analytics.

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IBM Big Data Hub

JANUARY 25, 2024

Considering that IDC surveyed 37% of companies that manage spare parts inventory by using spreadsheets, email, shared folders or an uncertain approach, it becomes evident that this practice carries more risk than it might seem. 2 Unless your demand forecasting is accurate, adopting a reactive approach might prove less efficient.

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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.

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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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Jet Global

OCTOBER 9, 2024

According to a recent Forbes article, “the prescriptive analytics software market is estimated to grow from approximately $415M in 2014 to $1.1B By harnessing the power of real-time data and analytics, organizations can detect shifts in their environment, make proactive adjustments, and better serve customers.

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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. Daniel Kahneman @ #dominorev #rev2 #keynote #DataScience #data #AccuLogique #data4good #analytics #ThisIsNYC pic.twitter.com/hb7huNLgC4. Because of compliance.

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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. The fill report is here: Leadership Vision for 2021: Data and Analytics. Some data is more a risk than valuable. On January 4th I had the pleasure of hosting a webinar.

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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?

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DataRobot Blog

MARCH 15, 2022

Integrating and aligning data across organizations (acute, primary, mental health, social care, and third sector) can be challenging, but is essential to enable forward-looking population health management, strengthen risk stratification, and support the redesign of care pathways.

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IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. Adoption is imperative to beat the competition, release innovative products and services, better meet customer expectations, reduce risk and fraud, and drive profitability. Start a trial. AI governance.

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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. Some examples of data science use cases include: An international bank uses ML-powered credit risk models to deliver faster loans over a mobile app.

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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. These professionals collaborate with IT teams, management, or data scientists to align analytical efforts with organizational objectives across various industries.

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Alation

AUGUST 26, 2021

Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more. Privacy, Risk and Compliance. Active metadata offers benefits like: Provides context around data’s past usage to support confident self-service analytics.

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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.’ What is a Cititzen Data Scientist? Who is a Citizen Data Scientist? What are Citizen Analysts?

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CIO Business Intelligence

APRIL 9, 2025

The foundational tenet remains the same: Untrusted data is unusable data and the risks associated with making business-critical decisions are profound whether your organization plans to make them with AI or enterprise analytics. Like most, your enterprise business decision-makers very likely make decisions informed by analytics.

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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.

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CIO Business Intelligence

DECEMBER 19, 2024

As organizations struggle with the increasing volume, velocity, and complexity of data, having a comprehensive analytics and BI platform offers real solutions that address key challenges, such as data management and governance, predictive and prescriptive analytics, and democratization of insights. Heres how they did it.

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CIO Business Intelligence

FEBRUARY 13, 2025

Artificial intelligence (AI)-enabled systems are driving a new era of business transformation, revolutionizing industries through prescriptive analytics, personalized customer experiences and process automation. Generative AI risks. Promoting fairness and inclusivity in AI systems builds trust and mitigates reputational risks.

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