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Ad:Tech 2022: Decoding a single source of truth for digital marketing measurement | Digital

The panel comprising Sonia Khurana, COO, Digitas, Rubeena Singh, country manager, Josh, and Monaz Todywalla, CEO, PHD India, touched upon the importance of unification of data for businesses

How big should a micro-service be? | The Bovine Synchrotron

SRP and my Head Many years ago, whilst working at an Investment Bank with a number of ThoughtWorks colleagues, we were thinking about how big objects should be. Obviously as developers we were thinking in terms of the Single Responsibility Principle, Open-Closed Principle and Separation of Concerns. I came up with a simple heuristic. Simply stated, an object should be no bigger than the size of my head when pressed up against the monitor – basically a screenful of code. Now, I have a fairly big head (but thats ok, cos there ain’t much inside it) so your mileage may vary.

Boost Business Analytics with an Operational Data Store | Transforming Data with Intelligence

Standardize how data is defined for users and applications Improve overall data quality Transform data for Bl and analytics. One of the main data-preparation challenges is that most organizations use several systems to handle data; this leads to a need for more sophisticated data integration methods and complicated data processing procedures. Fortunately, an operational data store (ODS) can provide the necessary capabilities that will allow an organization to integrate data from disparate, even geographically distant, sources. An ODS focuses on current data, which makes it ideal for operational decision-making. Designed to focus on a single product, service, or customer, the data in an ODS is constantly updated to ensure that it has the most current data. This means that data is updated several times each day without storing the history of changes.

Globe Telecom wins Cloudera 2020 Data Impact Awards

Globe Telecom wins Cloudera 2020 Data Impact Awards
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