CIO Business Intelligence

APRIL 27, 2023

At this time of dynamic business and market changes, uncertainty, and quickly evolving consumption models for IT infrastructure, every IT executive understands the benefits and necessity of network agility. We’ve seen how it can gather and organize telemetry data collected from all parts of a company’s network.

Management 98

Management Internet of Things Cost-Benefit Uncertainty 98

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations.

Machine Learning 220

Machine Learning Risk Management Statistics 220

Smart Data Collective

DECEMBER 17, 2021

The process of Marketing Analytics consists of data collection, data analysis, and action plan development. Understanding your marketing data to make more informed and successful marketing strategy decisions is a systematic process. Types of Data Used in Marketing Analytics. Preparing the Data for Analysis.

Marketing Analytics 95

Marketing Analytics Marketing Data-driven Analytics 95

Cloudera

APRIL 9, 2021

The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection. The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization. Data Collection – streaming data.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

IBM Big Data Hub

FEBRUARY 23, 2024

DL models can improve over time through further training and exposure to more data. When a user sends a message, the system uses NLP to parse and understand the input, often by using DL models to grasp the nuances and intent. DL, a subset of ML, excels at understanding context and generating human-like responses.

Enterprise 107

Enterprise Interactive Data-driven Key Performance Indicator 107

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

IBM Big Data Hub

FEBRUARY 7, 2024

2 For example, some are turning to software solutions that can more easily capture, manage and report ESG data. Circular economy: When waste is a resource Waste not, want not: the circular economy model, which aims to minimize unnecessary waste and make the most of resources, is booming. trillion in economic benefits by 2030.

Reporting 100

Reporting Cost-Benefit Internet of Things Data-driven 100

CIO Business Intelligence

APRIL 29, 2022

In this new era the role of humans in the development process also changes as they morph from being software programmers to becoming ‘data producers’ and ‘data curators’ – tasked with ensuring the quality of the input. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’

Data Governance 145

Data Governance IT Risk Data Lake 145

CIO Business Intelligence

APRIL 14, 2022

Digitizing operations, experiences, and products will not only save time and money, but also increase speed to insight by breaking down silos and making critical data more accessible. Smarter operations through integrated data and analytics. For example, a client in the oil and gas sector recently equipped their U.S.

Strategy 112

Strategy Digital Transformation IoT Measurement 112

CIO Business Intelligence

JUNE 5, 2023

Optimize internal technology Today, CIOs can influence everything from hardware procurement and the way developers write code for their company, to how IT gathers, processes, distributes and stores data—all of which impact a company’s carbon footprint. The CIO’s role in delivering this technology will be essential.

Software 106

Software Measurement Visualization Business Objectives 106

CIO Business Intelligence

SEPTEMBER 8, 2022

Most organizations understand the profound impact that data is having on modern business. 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.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

DataRobot

OCTOBER 20, 2021

Data literacy ensures that diverse perspectives are baked into AI governance and leads to the production of AI systems that achieve better and more consistent outcomes. It is a key component of developing responsible AI, and promotes trust not only in AI concepts but also in individual AI models. What Is Data Literacy?

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

CIO Business Intelligence

MARCH 21, 2022

As such, a data scientist must have enough business domain expertise to translate company or departmental goals into data-based deliverables such as prediction engines, pattern detection analysis, optimization algorithms, and the like. Semi-structured data falls between the two.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Structured Data 137

Smart Data Collective

APRIL 14, 2021

If you occasionally run business stands in fairs, congresses and exhibitions, business stands designers can incorporate business intelligence to aid in better business and client data collection. Business intelligence tools can include data warehousing, data visualizations, dashboards, and reporting.

Business Intelligence 133

Business Intelligence Dashboards Visualization Big Data 133

Cloudera

SEPTEMBER 23, 2021

Actually, that metric has dropped to three seconds since that study was conducted a decade ago. Organizational successes forged during the crisis need to be hardwired into the new operating model; leaders must ensure their organizations do not revert to old behaviors and processes.

Reporting 84

Reporting Metrics Sales Data Collection 84

Sisense

SEPTEMBER 3, 2020

Data Scientist. Data scientists usually build models for data-driven decisions asking challenging questions that only complex calculations can try to answer and creating new solutions where necessary. While salaries for data analysts are often reasonably high, salaries for data scientists may be higher still.

Statistics 97

Statistics Metrics Visualization Finance 97

FineReport

MAY 31, 2023

Contemporary dashboards surpass basic visualization and reporting by utilizing financial analytics to amalgamate diverse financial and accounting data, empowering analysts to delve further into the data and uncover valuable insights that can optimize cost-efficiency and enhance profitability.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

IBM Big Data Hub

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. How the models are stored.

Data Science 59

Data Science Machine Learning Cost-Benefit Deep Learning 59

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 59

Data mining Machine Learning Deep Learning Marketing 59

Jet Global

APRIL 2, 2019

Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing.

Enterprise 80

Enterprise OLAP Business Intelligence Internet of Things 80

Occam's Razor

JANUARY 12, 2015

Digital Analytics Ecosystem: Optimal Execution: Three Phases. Digital Analytics Ecosystem: Optimal Execution: Timing Expectations. At the core of everything you will do in digital analytics is the concept of metrics. How do you define a metric: It is simply a number. Your digital analytics tools are full of metrics.

Analytics 150

Analytics Slice and Dice KPI Metrics 150

CIO Business Intelligence

FEBRUARY 13, 2023

Measure performance of the current process by establishing a data collection plan to determine defects and gather metrics. By the end of this stage, it’s important to have a set of metrics for aligning with customer requirements and overall project goals.

Management 97

Management Statistics Manufacturing Measurement 97

Insight

JANUARY 14, 2020

a “pre-trained” model) to be recycled and reused for many different tasks. In short, I was faced with two major difficulties regarding data collection: I didn’t have nearly enough images, and the images I did have were not representative of a realistic gym environment. We pass 3 parameters: loss, optimizer , and metrics.

Metrics 58

Metrics Optimization Modeling Testing 58

Juice Analytics

MARCH 30, 2021

To bridge the gap between data and an audience, the data author has a complex job. The author must decide what data is most important to focus on to answer the questions at hand, and how to optimally harness and depict data to inform thinking and action. Effective communication with data is a rare skillset.

Cost-Benefit 131

Cost-Benefit Statistics Metrics Dashboards 131

Data Science 101

OCTOBER 31, 2019

Additionally, this will enable an organization to utilize resources optimally and enhance the customer’s experience. Data Mining Process. The complexity of the entire data mining mechanism can vary according to the size and kind of data an organization has and the aims that are required to be fulfilled. Data Collection.

Data mining 77

Data mining KDD Data Science Forecasting 77

AWS Big Data

FEBRUARY 26, 2024

When you start the process of designing your data model for Amazon Keyspaces, it’s essential to possess a comprehensive understanding of your access patterns, similar to the approach used in other NoSQL databases. It empowers businesses to explore and gain insights from large volumes of data quickly.

Dashboards 64

Dashboards Testing Metrics Optimization 64

Occam's Razor

APRIL 13, 2015

And, that's not all, when you consider that it is segmented data, across multiple dimensions, it really is impressive. But, I'm a big believer in optimizing data access to be at the right time as defined by your decision-making/action-taking speeds inside your company. You can see what's happening right now.

Analytics 155

Analytics Reporting Metrics Slice and Dice 155

Jet Global

AUGUST 14, 2019

And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions. So how is the data extracted?

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Jet Global

OCTOBER 2, 2019

And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions. So how is the data extracted?

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

IBM Big Data Hub

MARCH 29, 2024

Monitoring and optimizing application performance is important for software developers and enterprises at large. The more applications that an enterprise deploys, the more data that exists for collecting and analyzing. Analyzing telemetry data is key in understanding system performance and health. What is OpenTelemetry?

Metrics 85

Metrics Visualization Measurement Optimization 85

Occam's Razor

SEPTEMBER 15, 2014

Company UX leaders are happy to stink less by taking the sub-optimal path of responsive design, rather than create a mobile-unique experience (your customers tend to do different things on your desktop site than your mobile site!). In this post we will look mobile sites first, both data collection and analysis, and then mobile applications.

Metrics 141

Metrics Reporting Analytics Marketing 141

Occam's Razor

JULY 18, 2011

To not have it as an active part of your marketing portfolio is sub-optimal. The only requirement is that your mental model (and indeed, company culture) should be solidly rooted in permission marketing. Just to ensure you are executing against your right mental model. You must use metrics that are unique to the medium.

Metrics 137

Metrics Marketing Measurement Cost-Benefit 137

Occam's Razor

MAY 19, 2014

But the problem is that single golden metrics hide valuable insights and, more often than not, drive bad behavior. Here's my proposal: If you are pushed to have a single golden metric, give it a partner. The BFF metric you find should not be one that is very far away. So, great metric. Honestly, who can blame them.

Metrics 159

Metrics Key Performance Indicator Analytics Marketing 159

Ontotext

APRIL 4, 2019

Milena Yankova : We help the BBC and the Financial Times to model the knowledge available in various documents so they can manage it. They have different metrics for judging whether some content is interesting or not. This is a knowledge that anyone can get, but it would take much longer than optimal.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

O'Reilly on Data

MAY 14, 2020

Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model. In reality, many candidate models (frequently hundreds or even thousands) are created during the development process. Modelling: The model is often misconstrued as the most important component of an AI product.

Management 363

Management Experimentation B2B Machine Learning 363