CIO Business Intelligence

APRIL 22, 2022

For more details on data science bootcamps, see “ 15 best data science bootcamps for boosting your career.”. Data science certifications. Organizations need data scientists and analysts with expertise in techniques for analyzing data. Data science teams. Data science is generally a team discipline.

Data Science 137

Data Science Statistics Machine Learning Visualization 137

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics in business Predictive analytics draws its power from a wide range of methods and technologies, including big data, data mining, statistical modeling, machine learning, and assorted mathematical processes. from 2022 to 2028.

Predictive Analytics 138

Predictive Analytics Analytics Predictive Modeling Forecasting 138

Smart Data Collective

AUGUST 7, 2019

Big data has the power to transform any small business. However, many small businesses don’t know how to utilize it. 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.

Data Analytics 100

Data Analytics Analytics Big Data Data Lake 100

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 84

Predictive Analytics Sales Enterprise Predictive Modeling 84

IBM Big Data Hub

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. And you should have experience working with big data platforms such as Hadoop or Apache Spark.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

CIO Business Intelligence

JULY 26, 2023

Empowering agents with data Re/Max’s Ligon, who previously served as CIO of Prudential Real Estate and Berkshire Hathaway Home Services, oversees a cloud estate that includes Oracle Financials, Personify for membership management, and Inside Real Estate, a third-party industry SaaS platform tailored for brokers and agents.

Data Lake 93

Data Lake Digital Transformation Machine Learning Data Architecture 93

CIO Business Intelligence

JUNE 20, 2022

Otis One’s cloud-native platform is built on Microsoft Azure and taps into a Snowflake data lake. IoT sensors send elevator data to the cloud platform, where analytics are applied to support business operations, including reporting, data visualization, and predictive modeling.

Internet of Things 105

Internet of Things IoT Manufacturing Data Lake 105

CIO Business Intelligence

OCTOBER 13, 2023

Data scientist As companies embrace gen AI, they need data scientists to help drive better insights from customer and business data using analytics and AI. For most companies, AI systems rely on large datasets, which require the expertise of data scientists to navigate.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

CIO Business Intelligence

APRIL 25, 2022

Data Science Dojo. Data Science Dojo is one of the shortest programs on this list, but in just five days, Data Science Dojo promises to train attendees on machine learning and predictive models as a service, and each student will complete a full IoT project and have the chance to enter a Kaggle competition.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

IBM Big Data Hub

AUGUST 28, 2023

As it pertains to social media data, text mining algorithms (and by extension, text analysis) allow businesses to extract, analyze and interpret linguistic data from comments, posts, customer reviews and other text on social media platforms and leverage those data sources to improve products, services and processes.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

IBM Big Data Hub

OCTOBER 16, 2023

Foundation models can use language, vision and more to affect the real world. GPT-3, OpenAI’s language prediction model that can process and generate human-like text, is an example of a foundation model. They are used in everything from robotics to tools that reason and interact with humans.

Risk 77

Risk Modeling Management Metadata 77

AWS Big Data

MARCH 7, 2023

It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. Popular consumption entities in many organizations are queries, reports, and data science workloads.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

O'Reilly on Data

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Machine Learning 247

Machine Learning Testing Modeling Cost-Benefit 247

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 99

Metadata Visualization Unstructured Data Data mining 99

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task.

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106

CIO Business Intelligence

JUNE 22, 2022

The possibilities of data in motion are endless and will be explored in our upcoming webinar with Cloudera APAC Field CTO Daniel Hand , Are You Ready for the Future of Data in Motion? . Explore how your organisation’s data can convert into better business outcomes by signing up for our webinar here. .

IoT 84

IoT IT Manufacturing Internet of Things 84

Cloudera

NOVEMBER 2, 2020

Correlations across data domains, even if they are not traditionally stored together (e.g. real-time customer event data alongside CRM data; network sensor data alongside marketing campaign management data). The extreme scale of “big data”, but with the feel and semantics of “small data”.

Data Warehouse 91

Data Warehouse Optimization Dashboards Interactive 91

Alation

APRIL 14, 2022

A cloud environment with such features will support collaboration across departments and across common data types, including csv, JSON, XML, AVRO, Parquet, Hyper, TDE, and more. It’s More Important to Know What Your Data Means Than Where It Is. On-premises business intelligence and databases. Cloud governance.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

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 74

Visualization Interactive Modeling Machine Learning 74

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.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

datapine

NOVEMBER 27, 2019

Over the past decade, business intelligence has been revolutionized. Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

DECEMBER 4, 2019

Business intelligence has undergone many changes in the last decade. Each year, we hear about buzzwords that enter the community, language, market and drive businesses and companies forward. That’s why we have prepared a list of the most prominent business intelligence buzzwords that will dominate in 2020.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Rocket-Powered Data Science

SEPTEMBER 20, 2021

The data scientists need to find the right data as inputs for their models — they also need a place to write-back the outputs of their models to the data repository for other users to access. The data science team needs to know and to use that data which the BI team considers to be most important.

Data Science 285

Data Science Forecasting Business Intelligence Sales 285

AWS Big Data

JULY 28, 2023

Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools. He has 17 years of experience architecting, building, leading, and maintaining big data platforms.

Data Lake 65

Data Lake Data Governance Data Warehouse Modeling 65

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. There are many types of data pipelines, and all of them include extract, transform, load (ETL) to some extent.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

MAY 1, 2023

Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. Embedded Analytics Definition Embedded analytics are the integration of analytics content and capabilities within applications, such as business process applications (e.g., that gathers data from many sources.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52