CIO Business Intelligence

APRIL 11, 2024

Governments cannot put their head in the sand and ignore change, but they operate in a highly complex, data-sensitive environment and can’t afford to take on fundamental business risks in the name of innovation. You don’t have to risk resiliency to embrace innovation. You don’t have to rip out what’s working for your business.

Cost-Benefit 91

Cost-Benefit Predictive Analytics Data-driven Risk 91

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Smart Data Collective

JULY 16, 2023

The Imperative of Risk Mitigation A crucial element in the world of financial investments is effective hedge fund management. Optimizing hedge fund performance requires the implementation of intelligent strategies, from managing risks to maximizing returns, improving investor relations, and adapting to shifting market conditions.

ROI 71

ROI Data Analytics Analytics Risk Management 71

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Smart Data Collective

JUNE 8, 2023

The Evolution of Data Collection in Football Traditionally, football relied on basic statistics such as goals, assists, and possession percentages to evaluate performance. However, the advent of advanced technologies and analytics has ushered in a new era of data collection.

Data Analytics 82

Data Analytics Analytics Data Collection Statistics 82

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Smart Data Collective

APRIL 2, 2023

Their skills would certainly be valued by managerial staff who need to have ready access to healthcare statistics at all hours. Maintaining Predictive Analytics Software Dropshippers and online retailers have turned to predictive analytics solutions as a way to find out what products their clients are most likely to purchase.

Broadcasting 96

Broadcasting Marketing Technology Predictive Analytics 96

FineReport

MARCH 24, 2024

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. SAS automates statistical data analysis tasks and offers enhanced security features.

Statistics 52

Statistics Data mining Visualization Reporting 52

Smart Data Collective

AUGUST 10, 2021

. ‘Although companies in healthcare, IT and finance are some of the biggest investors in analytics technology, plenty of other sectors are investing in analytics as well. Analytics Becomes Major Asset to Companies Across All Sectors. The most significant benefit of statistical analysis is that it is completely impartial.

Data Analytics 136

Data Analytics Analytics Big Data Key Performance Indicator 136

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. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. All descriptive statistics can be calculated using quantitative data. Digging into quantitative data. This is quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Smart Data Collective

FEBRUARY 21, 2020

For example, most lenders have historically offered a wide range of different loan options to consumers ; but today, with better access to consumer data, lenders can do a more intelligent risk analysis of each individual customer. Market Analytics and Profitability. Customer Perks.

Big Data 120

Big Data Machine Learning Statistics Predictive Analytics 120

Smart Data Collective

DECEMBER 21, 2022

The Bureau of Labor Statistics estimates that there are nearly 106,000 employed data scientists in the United States. You can use big data to improve risk scoring models and use real-time analytics to stop threats. A growing number of data scientists are being employed in various industries to help solve many challenges.

IT 111

IT Big Data Data Science Data-driven 111

datapine

JANUARY 6, 2022

More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. Let’s quickly review the most common statistical terms: Mean: a mean represents a numerical average for a set of responses. Standard deviation: this is another statistical term commonly appearing in quantitative analysis.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

Smart Data Collective

AUGUST 15, 2019

The human resources department is in a unique position to help curb those statistics and ensure the workforce is strategically aligned with the cost factors of a business. Using data, you can identify your resignation rate and commonalities and correlations; use predictive analytics to determine risk of exit; and much more.

Big Data 83

Big Data Sales Testing Statistics 83

IBM Big Data Hub

AUGUST 7, 2023

In an ideal scenario, they would be able to, with relative and consistent accuracy, predict performance of clinical trial sites that are at risk of not meeting their recruitment expectations. Ultimately, enabling real-time monitoring of site activities and enrollment progress could prompt timely mitigation actions ahead of time.

Optimization 59

Optimization Forecasting Data-driven Strategy 59

CIO Business Intelligence

OCTOBER 18, 2023

The procedure, often called kidney dialysis, cleansing a patient’s blood, substituting for the function of the kidneys, and is not without risk, however. Clinically, prediction is more useful if it predicts an IDH event for a given patient during an ongoing dialysis treatment.

Predictive Analytics 132

Predictive Analytics Analytics Machine Learning Digital Transformation 132

Smarten

JUNE 28, 2018

Business Problem: A bank wants to group loan applicants into high/medium/low risk based on attributes such as loan amount, monthly installments, employment tenure, the number of times the applicant has been delinquent in other payments, annual income, debt to income ratio etc. Use Case – 1. Use Case – 2.

IT 40

IT Business Intelligence Predictive Modeling Risk 40

Cloudera

MARCH 2, 2018

Gain improved intelligence on operating context and needs through expanded use of descriptive analytics techniques. Identify those most at risk or most affected by a problem more accurately by using predictive analytics. The model has been shown to be effective in preventing the screening-out of at-risk children.

Data-driven 42

Data-driven Prescriptive Analytics Descriptive Analytics Machine Learning 42

Smarten

JUNE 27, 2018

For example, if an outlier indicates a risk or a mistake, that outlier should be identified and the risk or mistake should be addressed. All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists.

IT 40

IT Business Intelligence Predictive Modeling Testing 40

Domino Data Lab

JANUARY 24, 2019

This group of solutions targets code-first data scientists who use statistical programming languages and spend their days in computational notebooks (e.g., In a similar vein, in 2018 Forrester split apart its “Wave” for predictive analytics products into two distinct Waves. Code-first data science platforms.

Data Science 65

Data Science Marketing Data-driven Statistics 65

Smarten

JUNE 25, 2018

Loan applicants in a bank might be grouped as low, medium, and high risk applicants based on applicant age, annual income, employment tenure, loan amount, the number of times a payment is delinquent etc. About Smarten.

Enterprise 40

Enterprise IT Business Intelligence Predictive Modeling 40

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. pharmacogenomics) and risk assessment of genetic disorders (e.g., For example, an at-risk user Bob with churn score of 0.90 Summary.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

Smart Data Collective

AUGUST 8, 2019

Unfortunately, predictive analytics and machine learning technology is a double-edged sword for cybersecurity. FireEye claims that email is the launchpad for more than 90 percent of cyber attacks, while a multitude of other statistics confirm that email is the preferred vector for criminals.

Big Data 85

Big Data Data Processing Machine Learning Predictive Analytics 85

Smarten

JUNE 29, 2018

Based on these labels, the bank can easily make a decision on whether to give a loan to an applicant and the credit limit and interest rate each applicant is eligible for based on the amount of risk involved. Use Case – 2.

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 27, 2018

Based on these labels, the bank can easily make a decision on whether to give loan to an applicant and how much credit to extend, as well as the interest rate each applicant is eligible for based on the amount of risk involved. Use Case – 2.

Business Analytics 40

Business Analytics Analytics IT Business Intelligence 40

Smarten

JUNE 29, 2018

Based on these labels, the bank can easily make a decision on whether to give a loan to an applicant and the credit limit and interest rate for each applicant, based on the amount of risk. Use Case – 2.

Enterprise 40

Enterprise Business Intelligence Predictive Modeling Statistics 40

datapine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. What Is Business Intelligence And Analytics?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Smarten

JUNE 27, 2018

In this way, the riskier customers are identified easily and bank can avert the risk of delinquencies. Business Problem: Based on customer attributes and past online shopping behavioral data, an online retail giant wants to predict the future purchases of customers. Use Case – 2.

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

datapine

NOVEMBER 5, 2019

If you fail to do so, you risk damages in your productivity and costs. When you need to secure a beneficial and positive performance for your business, a business performance management dashboard will obtain advanced features such as predictive analytics. That kind of gamble is not the path of success.

Dashboards 220

Dashboards Cost-Benefit Sales Metrics 220

Rita Sallam

JULY 22, 2016

The risk of switching existing system of record reporting that is working may be higher than the benefit, so the 45% of you maintaining these systems makes sense, but increasing users and content? Q4: Are we going to discuss Predictive types of Analytics in this discussion?

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Predictive analytics, yeah, not so much.” You see these drivers involving risk and cost, but also opportunity.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Now, there is a data risk here.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines. It ranks high (No.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

datapine

AUGUST 29, 2022

However, don’t be deceived – just as you don’t need to be a literal startup to gain a lot of value from Eric Ries’ work, companies of all sizes and shapes can learn a lot of valuable information from “Lean Analytics”. 7) Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

IBM Big Data Hub

DECEMBER 20, 2023

Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences. In other words, ML leverages input data to predict outputs, continuously updating outputs as new data becomes available. temperature, salary).

Machine Learning 81

Machine Learning Modeling Deep Learning Predictive Modeling 81