AWS Big Data

JULY 13, 2023

Identifying key use cases After a number of preparation meetings to discuss business and technical aspects of the use case, AWS and Altron identified two uses cases to resolve their two business challenges: Business intelligence for business-to-business accounts – Altron wanted to focus on their business-to-business (B2B) accounts and customer data.

Optimization 88

Optimization B2B Data Quality Sales 88

Ontotext

MAY 22, 2023

Master data management (MDM), on the other hand, is focused on ensuring data quality and consistency across different systems and applications. MDM creates a single, verified source of data that can be used throughout an organization, and enforce policies and standards to maintain data quality.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

Occam's Razor

NOVEMBER 13, 2009

Some might argue, rightly so, that the most elusive thing to accomplish is to truly bring data democracy to your organization. This chapter bravely hopes to help you do exactly that: excite people about data, remove organizational barriers, use data to change behavior, dealing with data quality, and creating data driven HiPPO's.

Analytics 71

Analytics Metrics Measurement Testing 71

DataRobot Blog

APRIL 1, 2018

This shift is driving a hybrid data integration mentality, where business teams are given curated data sandboxes so they can participate in building future use cases such as mobile applications, B2B solutions, or IoT analytics. To achieve organization-wide data literacy, a new information management platform must emerge.

Analytics 40

Analytics IoT Internet of Things B2B 40

Occam's Razor

DECEMBER 12, 2016

Data quality plays a role into this. And, most of the time, regardless of the size of the size of the company, you only know your code is not working post-launch when data is flowing in (not!). You got me, I am ignoring all the data layer and custom stuff! All that is great.

Analytics 141

Analytics Data-driven Strategy Consulting 141

Occam's Razor

APRIL 21, 2014

The mistake we make is that we obsess about every big, small and insignificant analytics implementation challenge and try to fix it because we want 99.95% comfort with data quality. We wonder why data people are not loved. :). chapter 5 specifically provides advice on B2B and non-ecommerce websites). Six years go by.

Marketing Analytics 131

Marketing Analytics Marketing Analytics Measurement 131

Andrew White

JANUARY 9, 2022

– We see most, if not all, of data management being augmented with ML. Much as the analytics world shifted to augmented analytics, the same is happening in data management. You can find research published on the infusion of ML in data quality, and also data catalogs, data discovery, and data integration.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Occam's Razor

SEPTEMBER 21, 2015

When you are presenting, to an audience of 3 or 3,000, your goal should be to get the data out of the way as fast as you can, so that you can move to the so what conversation. Surely you are curious why the lovely hipster gentleman in a t-shirt was necessary to communicate with B2B bosses. A delightful mess.

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

datapine

JANUARY 31, 2022

The companies that are most successful at marketing in both B2C and B2B are using data and online BI tools to craft hyper-specific campaigns that reach out to targeted prospects with a curated message. Consumers have grown more and more immune to ads that aren’t targeted directly at them.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52