IBM Big Data Hub

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. Having the right data strategy and data architecture is especially important for an organization that plans to use automation and AI for its data analytics.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 101

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 101

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Birst BI

OCTOBER 30, 2018

This may involve integrating different technologies, like cloud sources, on-premise databases, data warehouses and even spreadsheets. Add the predictive logic to the data model. With the source data now fully integrated into an analytic model, add and test different predictive algorithms.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Sisense

JUNE 30, 2020

The simplest type, descriptive analytics , describes something that has already happened and suggests its root causes. This data is gathered into either on-premises servers or increasingly into cloud data warehouses and data lakes. A simple example would be the analysis of marketing campaigns.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Smart Data Collective

OCTOBER 13, 2021

Some solutions provide read and write access to any type of source and information, advanced integration, security capabilities and metadata management that help achieve virtual and high-performance Data Services in real-time, cache or batch mode. How does Data Virtualization complement Data Warehousing and SOA Architectures?

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Andrew White

JANUARY 11, 2021

Do you recommend a consulting approach strategy rather than a CDO strategy? How do you think Technology Business Management plays into this strategy? Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52