Google Cloud Data & Analytics

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Google Cloud Platform (GCP) Products & Services

Google Cloud Smart Analytics Platform is a flexible, open, and secure analytics platform that provides the easiest path to becoming an intelligence-driven organization. It builds on Google’s decades of innovation in AI and building internet-scale services, and is based on the same proven and reliable technology principles that power Google’s services (e.g. Search, Gmail, Maps, YouTube). Organizations choose Google Cloud to build their data cloud for its ability to fuel data-driven transformation like no other solution on the market today.

Data Integration

Data integration is the process that brings these separate data collections together in order to generate higher data value and insights.

Data integration is especially important as your business pursues digital transformation strategies, since your ability to improve operations, boost customer satisfaction, and compete in an increasingly digital world requires insight into all your data.

Data Governance

Data governance is a principled approach to managing data during its life cycle, from acquisition to use to disposal.

Every organisation needs data governance. As businesses throughout all industries proceed on their digital-transformation journeys, data has quickly become the most valuable asset they possess.

Data Lake

A data lake is a centralized repository designed to store, process, and secure large amounts of structured, semistructured, and unstructured data. It can store data in its native format and process any variety of it, ignoring size limits.

 

Business Intelligence

Business intelligence (BI) is the process of using the power of people and technologies to collect and analyse data to be used by organisations in their strategic and daily decision-making processes.

Data Warehouse

Data-driven companies require robust solutions for managing and analysing large quantities of data across their organizations. These systems must be scalable, reliable, and secure enough for regulated industries, as well as flexible enough to support a wide variety of data types and use cases. The requirements go way beyond the capabilities of any traditional database. That’s where the data warehouse comes in.

 

ETL

ETL stands for extract, transform, and load and is a traditionally accepted way for organizations to combine data from multiple systems into a single database, data store, data warehouse, or data lake. ETL can be used to store legacy data, or—as is more typical today—aggregate data to analyze and drive business decisions.

Predictive Analytics

Predictive analytics is the use of historical data, statistical algorithms, predictive modeling, and big data machine learning techniques to help organizations predict future outcomes more accurately, plan for unknown events, and discover opportunities in future activities.

 

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