CIO Business Intelligence

NOVEMBER 14, 2022

Decision support systems are generally recognized as one element of business intelligence systems, along with data warehousing and data mining. They emphasize access to and manipulation of large databases of structured data, often a time-series of internal company data and sometimes external data.

Data mining 141

Data mining Data-driven Statistics OLAP 141

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

Smart Data Collective

JUNE 11, 2019

Building a robust data platform can transform the way manufacturers handle their customers and supplies. Not only are real-time results available, but big data can also provide demand forecasts to guide the production chain based on historical data sales trends in order to stay on top of the demand.

Manufacturing 93

Manufacturing Analytics Big Data Data mining 93

Sisense

MARCH 14, 2021

As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data. IoT sensors on factory floors are constantly streaming data into cloud warehouses and other storage locations.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

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

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

Jet Global

MAY 9, 2024

The architecture may vary depending on the specific use case and requirements, but it typically includes stages of data ingestion, transformation, and storage. Data ingestion methods can include batch ingestion (collecting data at scheduled intervals) or real-time streaming data ingestion (collecting data continuously as it is generated).

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52