Smart Data Collective

AUGUST 7, 2019

Big data has the power to transform any small business. One study found that 77% of small businesses don’t even have a big data strategy. If your company lacks a big data strategy, then you need to start developing one today. Using Big Data to Fix Your Biggest Problems as a Business Owner.

Data Analytics 99

Data Analytics Analytics Big Data Data Lake 99

Rocket-Powered Data Science

JULY 13, 2023

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 167

Analytics Machine Learning Data Science Deep Learning 167

Smart Data Collective

MARCH 3, 2021

The legal sector is still in its infancy when it comes to big data and analytics. Lawyers and law experts are trying to figure it out, and consternation continues to shadow some corners because not everyone can quite understand what analytics is and how it can improve the personal injury law industry.

Analytics 126

Analytics Big Data Predictive Modeling Insurance 126

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. Without big data in predictive analytics, these descriptive models can’t offer a competitive advantage or negotiate future outcomes.

Predictive Analytics 121

Predictive Analytics Analytics Predictive Modeling Data mining 121

CIO Business Intelligence

APRIL 22, 2022

For most organizations, it is employed to transform data into value in the form of improved revenue, reduced costs, business agility, improved customer experience, the development of new products, and the like. Data science gives the data collected by an organization a purpose. Data science vs. data analytics.

Data Science 135

Data Science Statistics Machine Learning Visualization 135

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. from 2022 to 2028.

Predictive Analytics 133

Predictive Analytics Analytics Predictive Modeling Forecasting 133

Smart Data Collective

JULY 10, 2019

Big data is changing the nature of healthcare. One of the biggest developments was the implementation of the Medical Information Mart for Intensive Care , which took data from 50,000 patients dating back to 2001. Big data will have an even more profound impact in the near future.

Big Data 71

Big Data Measurement Predictive Modeling Manufacturing 71

Cloudera

NOVEMBER 18, 2020

It hosts over 150 big data analytics sandboxes across the region with over 200 users utilizing the sandbox for data discovery. With this functionality, business units can now leverage big data analytics to develop better and faster insights to help achieve better revenues, higher productivity, and decrease risk. .

Internet Publishing and Broadcasting 121

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 121

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 55

Machine Learning Data Science Statistics Deep Learning 55

CIO Business Intelligence

APRIL 25, 2022

WeCloudData is a data science and AI academy that offers a number of bootcamps as well as a diploma program and learning paths composed of sequential courses. Offerings include: a part-time and a full-time data science bootcamp, an AI engineering bootcamp, a part-time BI and data analytics bootcamp, and a data engineering bootcamp.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

IBM Big Data Hub

APRIL 1, 2024

Analyzing customer behavior for tailored product recommendations With the power of predictive analytics and GenAI, businesses can understand when specific customers are best suited for new products, receive suggestions for the appropriate products, and receive suggested next steps for engaging with the client.

Predictive Analytics 79

Predictive Analytics Sales Enterprise Predictive Modeling 79

Smart Data Collective

SEPTEMBER 26, 2021

Working with massive structured and unstructured data sets can turn out to be complicated. It’s obvious that you’ll want to use big data, but it’s not so obvious how you’re going to work with it. So, let’s have a close look at some of the best strategies to work with large data sets.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

Domino Data Lab

JULY 28, 2021

Data science is a field that uses math and statistics as part of a scientific process to develop an algorithm that can extract insights from data. All models are not made equal. At this stage, data scientists begin writing code for computation and model-building.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Domino Data Lab

OCTOBER 7, 2020

Danger of Big Data. Big data is the rage. This could be lots of rows (samples) and few columns (variables) like credit card transaction data, or lots of columns (variables) and few rows (samples) like genomic sequencing in life sciences research. The accuracy of any predictive model approaches 100%.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

CIO Business Intelligence

OCTOBER 13, 2023

In the next six to 12 months, some of the most popular anticipated uses for gen AI include content creation (42%), data analytics (53%), software development (41%), business insight (51%), internal customer support (45%), product development (40%), security (42%), and process automation (51%).

Deep Learning 142

Deep Learning Machine Learning Modeling Software 142

IBM Big Data Hub

MAY 17, 2024

Use case 1: AI for modernization and business model expansion AI-powered tools can be incredibly valuable in optimizing and modernizing business operations throughout the customer journey, but it is critical in the commerce continuum.  The applications of AI in commerce are vast and varied.

B2B 66

B2B Interactive Optimization Forecasting 66

Rocket-Powered Data Science

OCTOBER 6, 2023

The counterexample to the supervised learning explanation of precursor analytics is a “black swan” event – a rare high-impact event that is difficult to predict under normal circumstances – such as the global pandemic, which led to the failure of many predictive models in business. ” “Just 26.5%

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

datapine

DECEMBER 4, 2019

Moreover, as most predictive analytics capabilities available today are in their infancy — they have simply not been used for long enough by enough companies on enough sources of data – so the material to build predictive models on was quite scarce. Mobile Analytics. Augmented Analytics.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

IBM Big Data Hub

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

Machine Learning 49

Machine Learning Marketing Forecasting Modeling 49

IBM Big Data Hub

FEBRUARY 14, 2024

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. AIOps is one of the fastest ways to boost ROI from digital transformation investments.

Cost-Benefit 83

Cost-Benefit Insurance Unstructured Data Machine Learning 83

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

AWS Big Data

JANUARY 25, 2023

An Amazon Personalize job predicts for each line of input data (restaurants and restaurant articles) and produces ML-generated recommendations in the designated S3 output folder. The recommendation records are surfaced using interaction data, product data, and predictive models.

Visualization 78

Visualization Interactive Modeling Machine Learning 78

Alation

APRIL 14, 2022

Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. It’s More Important to Know What Your Data Means Than Where It Is.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. The term “ML” is No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Jet Global

MAY 1, 2023

Third-party data might include industry benchmarks, data feeds (such as weather and social media), and/or anonymized customer data. Four Approaches to Data Analytics The world of data analytics is constantly and quickly changing. Ideally, your primary data source should belong in this group.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52