IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Sisense

APRIL 26, 2020

In our modern digital world, proper use of data can play a huge role in a business’s success. Datasets are exploding at an ever-accelerating rate, so collecting and analyzing data to maximum effect is crucial. Companies and businesses focus a lot on data collection in order to make sure they can get valuable insights out of it.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

BizAcuity

MARCH 1, 2019

Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. This is where AI-based analysis and response play a critical role in extracting optimal value from the data. Bringing the power of AI to IoT.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Alation

FEBRUARY 20, 2020

By dramatically lowering the cost of storing data for analysis, it ushered in an era of massive data collection. By changing the cost structure of collecting data, it increased the volume of data stored in every organization. Disruptive Trend #2: Self-Service Analytics.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

Alation

MAY 16, 2023

Data Integration A data pipeline can be used to gather data from various disparate sources in one data store. This makes it easier to compare and contrast information and provides organizations with a unified view of their data. It’s worth noting that a data pipeline may have more than one data source.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Alation

MAY 16, 2023

Data Integration A data pipeline can be used to gather data from various disparate sources in one data store. This makes it easier to compare and contrast information and provides organizations with a unified view of their data. It’s worth noting that a data pipeline may have more than one data source.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69