CIO Business Intelligence

NOVEMBER 14, 2022

Decision intelligence seeks to update and reinvent decision support systems with a sophisticated mix of tools including artificial intelligence (AI) and machine learning (ML) to help automate decision-making. Forecasting models. XLSTAT is an Excel data analysis add-on geared for corporate users and researchers.

Data mining 144

Data mining Data-driven Statistics OLAP 144

CIO Business Intelligence

DECEMBER 13, 2023

The evolution of AI and the use of structured and unstructured data When discriminative AI rose to prominence in sectors such as banking, healthcare, retail, and manufacturing, it was primarily trained on and used to analyze, classify, or make predictions about unstructured data. What’s hiding in your unstructured data?

Unstructured Data 98

Unstructured Data IoT Metadata Manufacturing 98

IBM Big Data Hub

NOVEMBER 29, 2023

Furthermore, AI algorithms’ capacity for recognizing patterns—by learning from your company’s unique historical data—can empower businesses to predict new trends and spot anomalies sooner and with low latency.

Unstructured Data 94

Unstructured Data Data-driven ROI Machine Learning 94

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The company’s Findability.ai

Unstructured Data 106

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 106

IBM Big Data Hub

JULY 26, 2023

AI solutions work by collecting asset performance data and feeding it into machine learning models, which can predict asset health and risk of failure. AI helps address this problem by combining aspects like demand forecasting, last – mile delivery , and routing optimization.

Optimization 81

Optimization Manufacturing Cost-Benefit Risk 81

Cloudera

NOVEMBER 15, 2021

The International Data Corporation (IDC) estimates that by 2025 the sum of all data in the world will be in the order of 175 Zettabytes (one Zettabyte is 10^21 bytes). Most of that data will be unstructured, and only about 10% will be stored. Less will be analysed.

Unstructured Data 87

Unstructured Data Recreation/Entertainment Structured Data Reporting 87

IBM Big Data Hub

JULY 19, 2023

The explosion in digital data—in combination with declining availability of skilled and willing human resources to ingest and process the digital data in a compliant manner—is forcing life sciences organizations to explore AI, machine learning and now generative AI technologies.

Consulting 66

Consulting Machine Learning Manufacturing Optimization 66

IBM Big Data Hub

APRIL 18, 2023

At this year’s National Association of Broadcasters (NAB) convention, the IBM sports and entertainment team accepted an Emmy® Award for its advancements in curating sports highlights through artificial intelligence (AI) and machine learning (ML).

Recreation/Entertainment 78

Recreation/Entertainment Broadcasting Unstructured Data Consulting 78

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Cloudera

DECEMBER 15, 2017

Manufacturing can move from working with approximations to insight based on actual data, as it happens. Overall performance would be improved through better forecasts of product demand and production, through the understanding of plant operations across multiple metrics, and by being able to provide service and support to customers faster.

Manufacturing 40

Manufacturing IoT Machine Learning Data-driven 40

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. They can perform a wide range of different tasks, such as natural language processing, classifying images, forecasting trends, analyzing sentiment, and answering questions. versions).

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

Analytics Vidhya

AUGUST 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction The purpose of this article is to understand what is granger. The post Granger Causality in Time Series – Explained using Chicken and Egg problem appeared first on Analytics Vidhya.

Data Science 368

Data Science Publishing Analytics Forecasting 368

Analytics Vidhya

MAY 25, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Index Introduction Understanding Bitcoin Technologies used Getting real-time cryptocurrency data (bitcoin). The post Bitcoin Price Prediction Using Recurrent Neural Networks and LSTM appeared first on Analytics Vidhya.

Data Science 348

Data Science Publishing Technology Analytics 348

Analytics Vidhya

APRIL 26, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post How to check Stationarity of Data in Python appeared first on Analytics Vidhya. Introduction Hello readers! In our routine life, we come.

Data Science 224

Data Science Publishing Analytics Forecasting 224

Analytics Vidhya

JUNE 11, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Cutting straight right to the chase, Hurst exponent is a. The post Using Hurst Exponent to analyse the Stock and Crypto market with Python appeared first on Analytics Vidhya.

Marketing 189

Marketing Data Science Publishing Analytics 189

Analytics Vidhya

APRIL 27, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction: Hello Readers! Ever wonder what are the factors which. The post Impact of Global Stock Market on Indian stock Index in R appeared first on Analytics Vidhya.

Marketing 169

Marketing Data Science Publishing Analytics 169

Analytics Vidhya

MAY 20, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Time series data consists of a set of observations in which. The post Working with Stock Market Time Series Data using Facebook Prophet appeared first on Analytics Vidhya.

Marketing 150

Marketing Data Science Publishing Analytics 150

Analytics Vidhya

JUNE 24, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon “Time flies over us, but leave its shadow behind” a beautiful. The post Deep Dive into Time Series Data with Single Neuron appeared first on Analytics Vidhya.

Data Science 144

Data Science Publishing Analytics IT 144

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. Before selecting a tool, you should first know your end goal – machine learning or deep learning.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

FineReport

JULY 18, 2022

Except for the rows and columns, you can also display your data through graphs and charts. For more advanced data analysis, Excel provides you with pivot tables, enabling you to analyze structured data through multiple dimensions quickly and effectively. SAS Forecasting. From SAS Forecast Server. From KNIME.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

AWS Big Data

APRIL 2, 2024

Without the right metadata and documentation, data consumers overlook valuable datasets relevant to their use case or spend more time going back and forth with data producers to understand the data and its relevance for their use case—or worse, misuse the data for a purpose it was not intended for.

Metadata 85

Metadata Metrics Data-driven Modeling 85

Smart Data Collective

FEBRUARY 3, 2021

Big data algorithms that understand these principles can use them to forecast the direction of the stock market. Automatic trading, which hugely relies on artificial intelligence and bots, and trading that operates on machine learning are eliminating the human emotion factor from all this.

Big Data 139

Big Data Marketing Data Analytics Analytics 139

AWS Big Data

FEBRUARY 20, 2024

In this post, we discuss how to architect a near-real-time analytics solution with AWS managed analytics, AI and machine learning (ML), and database services. Solution overview The most common workloads, agnostic of industry, involve transactional data.

Visualization 95

Visualization Cost-Benefit Optimization B2B 95

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Metadata 87

Metadata Big Data Optimization Unstructured Data 87

AWS Big Data

APRIL 19, 2023

Every day, customers are challenged with how to manage their growing data volumes and operational costs to unlock the value of data for timely insights and innovation, while maintaining consistent performance. As data workloads grow, costs to scale and manage data usage with the right governance typically increase as well.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

MARCH 26, 2024

This can be achieved using AWS Entity Resolution , which enables using rules and machine learning (ML) techniques to match records and resolve identities. With QuickSight, you can embed dashboards to external websites and applications , and the SPICE engine enables rapid, interactive data visualization at scale.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Jet Global

MAY 9, 2024

Data Migration Pipelines : These pipelines move data from one system to another, often for the purpose of upgrading systems or consolidating data sources. For example, migrating customer data from an on-premises database to a cloud-based CRM system. What is an ETL pipeline?

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52