Smart Data Collective

MARCH 3, 2023

Then, you make adjustments based on what’s working within your business model— and what isn’t. It’s important to get an objective look at where there are shortcomings in your business model. That’s where modern data tools come in. Using Data to Find Shortcomings & Opportunities No business model is perfect.

Modeling 83

Modeling Cost-Benefit Software Strategy 83

CIO Business Intelligence

APRIL 29, 2022

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Data Centricity. Once built, the computational models should remain relatively static.

Data Governance 144

Data Governance IT Risk Data Lake 144

CIO Business Intelligence

JANUARY 25, 2023

Retiring redundant toolsets and establishing one source of truth for data collection and correlation across multi-vendor technologies. Research shows that, when following this maturity model for advancing network monitoring capabilities, organizations typically invest around $2.6 million per year. million and an ROI of 160%.

IT 82

IT Cost-Benefit ROI Software 82

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 87

Machine Learning Modeling Metadata Recreation/Entertainment 87

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

CIO Business Intelligence

APRIL 1, 2022

There is no need to pre-process data, train or hypertune machine learning models, nor load balance or manually provision your infrastructure to handle unpredictable traffic spikes. Retail Search: a market share and data play. These are machine learning algorithms; the more data collected the better the results,” she said.

IT 101

IT Machine Learning Cost-Benefit Data Collection 101

Dataiku

OCTOBER 19, 2021

Between energy diversity, climate challenges, and growth in electricity consumption, energy producers and suppliers must constantly optimize their processes and anticipate demand in order to adjust their offers, a strategy based on massive data collection and the deployment of AI solutions.

Modeling 105

Modeling Data Collection Data Science Optimization 105

CIO Business Intelligence

AUGUST 5, 2022

A hybrid approach is clearly established as the optimal operating model of choice. Many organizations set out on the modernization journey guided by the premise that cloud-first or cloud-only is the ultimate destination, only to find that the path is not appropriate for all data and workloads.

IT 89

IT Manufacturing Business Objectives Cost-Benefit 89

Smart Data Collective

AUGUST 25, 2022

In just a few years, billions of devices will be connected to the internet, collecting and sharing data. The IoT empowers organizations with real-time information that was once too expensive or difficult to collect. For businesses, these considerations include data privacy, security, and liability.

IoT 127

IoT Internet of Things IT Manufacturing 127

CIO Business Intelligence

JULY 6, 2023

Data collected from more than 1,000 survey respondents indicates that IT leaders have come to realize there is simply no one environment that works best for all applications. And today, only 48% of survey respondents said they have any apps in the cloud at all. Hybrid IT is a destination. What should organizations do?

IT 52

IT Data Processing Strategy Data Collection 52

Rocket-Powered Data Science

MAY 21, 2024

To see this, look no further than Pure Storage , whose core mission is to “ empower innovators by simplifying how people consume and interact with data.” However, this data was still left mostly unexploited for its maximum potential and enterprise-wide business value.

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

Jedox

JANUARY 19, 2023

Too many organizations around the world have a plan that doesn’t match their actual business model and structure. IBP solutions, such as Jedox, do this by automating data collection and integrating it into one platform. Sixty users at Fiat from different departments can now access high-quality data in one place.

IT 86

IT Forecasting Data Lake Marketing 86

Rocket-Powered Data Science

JULY 6, 2021

In at least one way, it was not different, and that was in the continued development of innovations that are inspired by data. This steady march of data-driven innovation has been a consistent characteristic of each year for at least the past decade. 2) MLOps became the expected norm in machine learning and data science projects.

Machine Learning 279

Machine Learning Data-driven IoT Deep Learning 279

CIO Business Intelligence

SEPTEMBER 2, 2022

If you’re an IT pro looking to break into the finance industry, or a finance IT leader wanting to know where hiring will be most competitive, here are the top 10 in-demand tech jobs in finance, according to data from Dice. As demand for tech skills grows in the finance industry, certain IT jobs are becoming more sought-after than others.

Finance 98

Finance IT Software Reporting 98

Rocket-Powered Data Science

JULY 13, 2023

Data is more than just another digital asset of the modern enterprise. So, what happens when the data flows are not quarterly, or monthly, or even daily, but streaming in real-time? Well, it soon became clear that the real problem was the reverse: how can we have our business move at the speed of our data?

Analytics 167

Analytics Machine Learning Data Science Deep Learning 167

CIO Business Intelligence

AUGUST 31, 2022

If you’re an IT pro looking to break into the finance industry, or a finance IT leader wanting to know where hiring will be most competitive, here are the top 10 in-demand tech jobs in finance, according to data from Dice. As demand for tech skills grows in the finance industry, certain IT jobs are becoming more sought-after than others.

Finance 98

Finance IT Software Reporting 98

Jet Global

DECEMBER 6, 2019

Creating reports inside the SAP ecosystem involves the careful collection and integration of data in ways that only IT knows how to connect. It may seem absolutely necessary that tech professionals be required for a complex, data-driven process like reporting. Things aren’t any better for the IT department.

Reporting 98

Reporting IT Key Performance Indicator Finance 98

CIO Business Intelligence

MAY 29, 2024

Because large enterprises use massive amounts of data, this critical asset can quickly become unmanageable and can sabotage the accuracy and efficiency of hard-working sales teams. Not only can AI tame unmanageable data but it can exponentially increase the value add of this critical asset across the business.

Sales 79

Sales Modeling Machine Learning Measurement 79

CIO Business Intelligence

FEBRUARY 12, 2024

This can help to solve the problem of centralized data collection, which is otherwise an impractical approach to a diverse array of data sources, encompassing vehicles, factories, individuals and the environment, and countless other sensors. What are Large Language Models (LLMs)?

Technology 108

Technology Interactive Visualization Modeling 108

Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Datasphere is not just for data managers.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

Rocket-Powered Data Science

MARCH 19, 2021

How to make smarter data-driven decisions at scale : [link]. The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. One CIO said it this way , “If CIOs invested in machine learning three years ago, they would have wasted their money. trillion by 2030.

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

O'Reilly on Data

JULY 28, 2020

Fair warning: if the business lacks metrics, it probably also lacks discipline about data infrastructure, collection, governance, and much more.) There’s a substantial literature about ethics, data, and AI, so rather than repeat that discussion, we’ll leave you with a few resources. Identifying the problem.

Marketing 362

Marketing Experimentation Metrics Testing 362

Rocket-Powered Data Science

JULY 6, 2021

Specifically, in the modern era of massive data collections and exploding content repositories, we can no longer simply rely on keyword searches to be sufficient. One type of implementation of a content strategy that is specific to data collections are data catalogs. Data catalogs are very useful and important.

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

CIO Business Intelligence

FEBRUARY 9, 2024

Like many other professional sports leagues, the NFL has been at the leading edge of data-driven transformation for years. During practices, it processes around 15,000 miles of player tracking data per week — translating to more than 500 million data points. During each week of games, Digital Athlete captures and processes 6.8

Recreation/Entertainment 130

Recreation/Entertainment Data-driven Risk Digital Transformation 130

Smart Data Collective

MAY 16, 2022

Data is becoming more important to modern organizations than ever before. One poll found that 74% of companies feel they are still struggling to use data effectively. One of the problems is that they don’t manage their data well. How Companies Can Manage their Data Better.

Management 127

Management Data mining Data Warehouse Data Collection 127

CIO Business Intelligence

JULY 3, 2023

Data exists in ever larger silos, but real knowledge still resides in employees. But the rise of large language models (LLMs) is starting to make true knowledge management (KM) a reality. These models can extract meaning from digital data at scale and speed beyond the capabilities of human analysts.

Management 103

Management Experimentation Modeling Enterprise 103

O'Reilly on Data

NOVEMBER 13, 2019

While Jonas applauds such inquiry and thinking deeply about the social ramifications of AI research, he is concerned the questions might be reinventing the wheel: “The data collection itself often has serious ramifications that we’ve all been wrestling with for 15 years. ” ( 2:12 ).

Machine Learning 183

Machine Learning Data Collection Modeling IT 183

CIO Business Intelligence

JUNE 3, 2024

The study surveyed 200+ IT and financial leaders who have implemented a FinOps model across many industries, and the findings focus on best practices for maximizing ROI on cloud infrastructure and applications. Data also shows partners are key in controlling runaway costs and gaining efficiencies in financial management. The problem?

Cost-Benefit 63

Cost-Benefit ROI Optimization Software 63

CIO Business Intelligence

NOVEMBER 1, 2023

There’s indeed a lot of hype around the latest wave of large language models (LLM) and associated tools, yet beneath the noise, there’s a whisper about how the technology will one day become indispensable. One common shortcoming of the basic setup of predictive maintenance is that rare events are underrepresented in the training data.

Enterprise 118

Enterprise Digital Transformation Modeling Interactive 118

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

CIO Business Intelligence

JANUARY 17, 2024

The first was becoming one of the first research companies to move its panels and surveys online, reducing costs and increasing the speed and scope of data collection. The first was becoming one of the first research companies to move its panels and surveys online, reducing costs and increasing the speed and scope of data collection.

Digital Transformation 112

Digital Transformation Dashboards Reporting Data Science 112

Smart Data Collective

MAY 29, 2023

Making data bias significantly concerns and directly influences the performance and fairness of AI translation systems. When you leave data bias unaddressed, it perpetuates discriminatory outcomes and undermines the credibility of AI translation.

Metrics 68

Metrics Measurement Data Collection Strategy 68

Smart Data Collective

MAY 29, 2023

With these changes comes the challenge of understanding how to gather, manage, and make sense of the data collected in various markets. With the introduction and use of machine learning, AI tech is enabling greater efficiencies with respect to data and the insights embedded in the information.

Data Collection 76

Data Collection Big Data Statistics Software 76

O'Reilly on Data

DECEMBER 10, 2019

We can collect many examples of what we want the program to do and what not to do (examples of correct and incorrect behavior), label them appropriately, and train a model to perform correctly on new inputs. Nor are building data pipelines and deploying ML systems well understood. Instead, we can program by example.

Software 261

Software Machine Learning Risk Data-driven 261

Insight

MARCH 12, 2020

The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. finished his first novel, Cuckoo’s Calling. labels).

Modeling 59

Modeling Metadata Publishing Sales 59

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Why AI software development is different.

Management 333

Management Machine Learning Experimentation Metrics 333

Cloudera

MAY 9, 2019

The report created a readiness model with five dimensions and various metrics under each dimension. The five dimensions of the readiness model are –. Data readiness – These set of metrics help you measure if your organization is geared up to handle the sheer volume, variety and velocity of IoT data.

IoT 56

IoT Modeling Metrics Measurement 56