O'Reilly on Data

JULY 28, 2020

This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage. One mid-sized digital media company we interviewed reported that their Marketing, Advertising, Strategy, and Product teams once wanted to build an AI-driven user traffic forecast tool.

Marketing 363

Marketing Experimentation Metrics Testing 363

CIO Business Intelligence

MAY 24, 2023

If the data is correctly curated and formatted, it can be used by data analytics and, in particular, AI to make recommendations that help an organization make decisions ahead of the market. Poor data quality leads to poor decisions and recommendations. Without frameworks, people tend to protect their data,” she says.

Data Governance 98

Data Governance Data Quality Data Collection Publishing 98

Smart Data Collective

JANUARY 9, 2023

Machine learning is a particular type of AI-powered software that has the ability to learn from the data it comes into contact with and become more capable of accurately forecasting results and outcomes over time.

Machine Learning 126

Machine Learning Software Strategy Marketing 126

CIO Business Intelligence

JUNE 7, 2022

In business, when a trend is forecast to grow by more than 3000% and generate cost savings of $7.3 In large financial services organizations, this data includes everything from earnings reports to projections, contracts, social media, marketing, and investments. Ready to evolve your analytics strategy or improve your data quality?

Unstructured Data 86

Unstructured Data Deep Learning Insurance Interactive 86

DataRobot

JUNE 1, 2021

In an earlier post, I shared the four foundations of trusted performance in AI : data quality, accuracy, robustness and stability, and speed. You should first identify potential compliance risks, with each additional step again tested against risks. Like a weather forecast, AI predictions are inherently probabilistic.

Uncertainty 52

Uncertainty Machine Learning Advertising Risk 52

FineReport

MARCH 24, 2024

Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making. Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. JPMorgan Chase & Co.:

Statistics 52

Statistics Data mining Visualization Reporting 52

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

Octopai

JANUARY 21, 2020

Complete data lineage on OLAP cube. For instance, it can be used when preparing to forecast inventory across regions, business units – all over a length of time, which requires a multi-dimensions analysis and the use of data perspectives from different angles. Who are the main stakeholders of cube data lineage reports?

OLAP 56

OLAP Metadata Online Analytical Processing Data Quality 56

CIO Business Intelligence

SEPTEMBER 8, 2022

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.

Cost-Benefit 110

Cost-Benefit Internet of Things Data-driven Data Lake 110

Jet Global

JULY 5, 2023

And on the other, internal pressures like the need for more frequent, accurate forecasting force CFOs to re-evaluate their existing tools and processes. With heightened scrutiny on organizations and leaders, organizations can’t afford such a high risk of error. And manual processes increase the likelihood of reporting mistakes.

Finance 52

Finance Uncertainty Reporting Marketing 52

FineReport

APRIL 26, 2023

Predictive Analytics assesses the probability of a specific occurrence in the future, such as early warning systems, fraud detection, preventative maintenance applications, and forecasting. Unlike traditional databases, processing large data volumes can be quite challenging. How to Choose the Right Big Data Analytics Tools?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Smart Data Collective

SEPTEMBER 25, 2019

However, according to a 2018 North American report published by Shred-It, the majority of business leaders believe data breach risks are higher when people work remotely. Whether you work remotely all the time or just occasionally, data encryption helps you stop information from falling into the wrong hands.

Technology 86

Technology Statistics Strategy Insurance 86

bridgei2i

FEBRUARY 21, 2019

A strong case study where a global MNC used AI enabled deal classification, data input enhancement, account analytics, and external data feeds to transform their sales organization in Nigeria resulting in “a substantial increase in sales productivity and forecasted Y-o-Y revenue growth.” Voice data quality).

Sales 40

Sales Structured Data Forecasting Enterprise 40

FineReport

MAY 31, 2023

Budget variance quantifies the discrepancy between budgeted and actual figures, enabling forecasters to make more accurate predictions regarding future costs and revenues. Finance and accounting teams often deal with data residing in multiple systems, such as accounting software, ERP systems, spreadsheets, and data warehouses.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

DataKitchen

DECEMBER 9, 2022

In addition to monitoring the performance of data-related systems, DataOps observability also involves the use of analytics and machine learning to gain insights into the behavior and trends of data. By using DataOps, organizations can improve. Query> When do DataOps?

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

O'Reilly on Data

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. We’re not encouraging skepticism or fear, but companies should start AI products with a clear understanding of the risks, especially those risks that are specific to AI.

Enterprise 281

Enterprise Modeling Testing Reporting 281

Cloudera

SEPTEMBER 7, 2023

But it’s also fraught with risk. This June, for example, the European Union (EU) passed the world’s first regulatory framework for AI, the AI Act , which categorizes AI applications into “banned practices,” “high-risk systems,” and “other AI systems,” with stringent assessment requirements for “high-risk” AI systems.

Insurance 83

Insurance Risk Data-driven Finance 83

CIO Business Intelligence

NOVEMBER 2, 2023

Still, 94% of technical leaders say they should be getting more value from their data and 78% say their organizations struggle to drive business priorities with data. I need to know my forecast. Data Governance, Data Management, Generative AI If I’m a sales leader, I need to know my pipeline.

Data Strategy 126

Data Strategy Strategy Sales Data Governance 126

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

IBM Big Data Hub

DECEMBER 7, 2023

Slice-and-dice analysis : OLAP allows users to slice and dice data along various dimensions, isolating specific segments for in-depth analysis. Improved decision-making Strategic planning and forecasting : OLAP helps businesses identify trends, patterns and potential risks, enabling better strategic planning and forecasting.

OLAP 58

OLAP Slice and Dice Cost-Benefit Data Warehouse 58

CIO Business Intelligence

APRIL 1, 2022

Consider that it may be easier to make one big decision well, rather than hundreds of smaller decisions that each have different payouts and risks. For example, buying stock in one company involves determining which stock will provide the best results, balanced with risk. Just starting out with analytics?

Data-driven 82

Data-driven Deep Learning Risk Optimization 82

Alation

MARCH 21, 2023

Data security The travel industry collects, transmits, processes, and stores a wide range of personally identifiable information (PII) from customers, which are of interest to bad actors, as cybercriminals target this valuable data. Otherwise, they risk a data privacy violation.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Jet Global

OCTOBER 27, 2020

For many organizations, exception reporting serves as a mechanism for alerting management when the organization is at risk of missing key performance targets. Data Quality. According to Gartner , poor data quality costs the average company about $15 million each year. That can lead to further data quality problems.

Reporting 52

Reporting Data Quality Cost-Benefit Sales 52

Jet Global

JANUARY 3, 2020

Anyone involved with business intelligence forecasting , for example, understands the struggle of insufficient data. Since the future waits for no one, most companies can’t afford to delay producing forecasts, which is why many sprint through the process while incorporating the minimum amount of information possible.

Business Intelligence 69

Business Intelligence Forecasting Data-driven Metrics 69

IBM Big Data Hub

OCTOBER 12, 2023

Worldwide IDC Global DataSphere Forecast, 2022–2026: Enterprise Organizations Driving Most of the Data Growth, May 2022 The post How data stores and governance impact your AI initiatives appeared first on IBM Blog. Learn more about IBM watsonx 1.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. QuickSight offers scalable, serverless visualization capabilities.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

Jet Global

MARCH 13, 2020

In a Deloitte survey, 67 percent of the 1,048 executives who participated said they were uncomfortable accessing data using the tools they have available. They prefer to ask an accountant or someone from IT to retrieve data for them. Worse, those consequences are now more probable with data volumes rising rapidly.

Finance 64

Finance Snapshot Reporting Advertising 64

FineReport

MAY 25, 2023

These data play a crucial role in enabling HR to make informed hiring decisions while enhancing forecasting and planning effectiveness. FineReport also supports data validation, ensuring data accuracy and integrity. Users can set up validation rules to enforce data consistency and completeness.

Dashboards 52

Dashboards Metrics Cost-Benefit Key Performance Indicator 52

datapine

AUGUST 29, 2022

The book has three main ideas: The biggest risk your company faces is investing a lot of time and resources into building something that the market doesn’t want. and this book will give you an insight into their data collecting procedures and the reasons behind them. Product/market fit is THE most important factor to get right.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Jet Global

MARCH 4, 2020

While this is important, what if you could grow your bottom line without having to take on expansion risks? Demand Forecasting – This manufacturing metric is used by companies to estimate the amount of raw materials they will require to meet future customer demand. Now it is time to look at some data management best practices.

Manufacturing 80

Manufacturing Metrics Reporting KPI 80

Andrew White

JANUARY 12, 2021

Predicts 2021: Data and Analytics Leaders Are Poised for Success but Risk an Uncertain Future : By 2023, 50% of chief digital officers in enterprises without a chief data officer (CDO) will need to become the de facto CDO to succeed. Through 2023, up to 10% of AI training data will be poisoned by benign or malicious actors.

Analytics 144

Analytics Metadata Enterprise Data-driven 144

Cloudera

JULY 20, 2021

Technology drives the ability to use enterprise data to make choices, decisions and investments – which then produce competitive advantage. Risk models for financial institutions and insurers are exponentially more complicated . GDP forecasts keep rising and falling.

Manufacturing 106

Manufacturing Forecasting IoT Insurance 106

datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Alation

JANUARY 27, 2022

Raw data includes market research, sales data, customer transactions, and more. Analytics can identify patterns that depict risks, opportunities, and trends. And historical data can be used to inform predictive analytic models, which forecast the future. Establishes Trust in Data. Inform Decision Making.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

Alation

OCTOBER 12, 2021

Enterprise data analytics enables businesses to answer questions like these. It empowers analysts to model scenarios, forecast change, and predict impact of real or imagined events. Having a data analytics strategy is a key to delivering answers to these questions and enabling data to drive the success of your business.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

datapine

DECEMBER 4, 2019

Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212