Peter James Thomas

AUGUST 29, 2018

Today I am talking to Christopher Bannocks , who is Group Chief Data Officer at ING. As stressed in other recent In-depth interviews [1] , data is a critical asset in banking and related activities, so Christopher’s role is a pivotal one. 2] I was asked to help solve the data problem.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Ontotext

MAY 5, 2023

Knowledge Representation In the context of the Financial Services Industry domain, the most popular examples of such data are entity (Who?) These two key data elements are used in approximately 80% of the use cases in the sector. Integrating reporting to move to a more streamlined, efficient approach to data collection.

Data Collection 64

Data Collection Risk Data-driven Interactive 64

erwin

APRIL 18, 2019

California Consumer Privacy Act (CCPA) compliance shares many of the same requirements in the European Unions’ General Data Protection Regulation (GDPR). Data governance , thankfully, provides a framework for compliance with either or both – in addition to other regulatory mandates your organization may be subject to.

Data Governance 81

Data Governance Metadata Data-driven Data Collection 81

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 71

Data Strategy Strategy Data Warehouse Prescriptive Analytics 71

Ontotext

MAY 18, 2020

Ever since Hippocrates founded his school of medicine in ancient Greece some 2,500 years ago, writes Hannah Fry in her book Hello World: Being Human in the Age of Algorithms , what has been fundamental to healthcare (as she calls it “the fight to keep us healthy”) was observation, experimentation and the analysis of data.

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

Timo Elliott

JANUARY 22, 2019

We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s. They bring insights to users rather than forcing users to unearth elusive trends, and provide more intuitive interfaces that make it easier to get the data people need to do their jobs.

Analytics 89

Analytics Machine Learning Unstructured Data Digital Transformation 89

FineReport

JULY 18, 2022

In an era full of data, data analysis allows us to discover the most useful information and make more scientific decisions for business operations. Data analysis tools are widely used by data analysts as well as non-professional business people to achieve better performance and higher efficiency. FineRepor t.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

Cloudera

JANUARY 11, 2018

For them, they may understand that they need a data-driven strategy or the culture may aim to take a shift to being guided by data. While it is true you can buy a BI or analytics tool that will analyze data in different locations, we believe that their are expressed benefits to combining data in a physical location.

Strategy 40

Strategy Data Warehouse Cost-Benefit Marketing 40

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

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 261

Machine Learning Software Metadata Testing 261

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52