Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

MARCH 26, 2024

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. 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.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

CDW Research Hub

APRIL 28, 2020

As businesses strive to become modern data-driven organizations, many are drawn to the value that a data platform in the cloud can provide. Cloud data platforms provide the speed, performance and scalability that is required to handle an exponential growth in volume of data.

Data-driven 52

Data-driven Analytics Consulting ROI 52

FineReport

MAY 30, 2024

In today’s data-driven world, the data visualization specialist plays a pivotal role in transforming complex information into visually appealing formats. The demand for skilled professionals in this field is rapidly increasing as businesses rely more on data for decision-making and operations.

Visualization 52

Visualization Dashboards KPI Reporting 52

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. And so will your data. You know the story well: you have a ton of data and need fast access to the right data. Building an efficient solution for data storage and processing is becoming more than just a back-office or IT challenge. Benefits of a Data Lake.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Cloudera

JULY 26, 2021

With this first article of the two-part series on data product strategies, I am presenting some of the emerging themes in data product development and how they inform the prerequisites and foundational capabilities of an Enterprise data platform that would serve as the backbone for developing successful data product strategies.

Strategy 119

Strategy Data Science Marketing Unstructured Data 119

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

NOVEMBER 25, 2020

The challenges Matthew and his team are facing are mainly about access to a multitude of data sets, of various types and sources, with ease and ad-hoc, and their ability to deliver data-driven and confident outcomes. . Most of their research data is unstructured and has a lot of variety. Challenges Ahead.

Data Warehouse 59

Data Warehouse Unstructured Data Analytics Visualization 59

Sisense

JULY 23, 2021

During this period, those working for each city’s Organising Committee for the Olympic Games (OCOG) collect a huge amount of data about the planning and delivery of the Games. At the Information, Knowledge, and Games Learning (IKL) unit, we anticipate collecting about 1TB of data from primary sources.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105