Google is one of the pioneers in harnessing the power of data. Over the years google has put its research and development strength to build data platform that touches the lives of billions of people around the world every day. It was inevitable for google to build a data platform that can collect and process data from billions of interactions made every day by the users. The platform has evolved over the years in almost every aspect of data processing be it storing the data, processing the data or generating real time insights.
Storing and processing have been critical as google utilizes data to understand user behaviors and providing experiences that were expected of it. This need lead to creation of data processing echo system that is robust, scalable and highly efficient in processing data. The google data innovation spanned across various areas on data processing. Data storage GFS to Colossus, one white paper from google team gave birth to HDFS and Hadoop. As google was benefitting from ability to process large amount of data using map-reduce frame, it realized the opportunity to utilize the unused processing capacities on data nodes, hence came Colossus. With change to storage there was need to find better data processing paradigm. This led to the development of Dremel and Flume.
The drive to provide best customer experience to users meant gaining insights from tons of data and act in real time. Gathering insight was no easy task, it was like find needle in a hay stack. Google created machine learning libraries and frameworks to understand customer behavior and give them what they want. This meant understanding what they say and respond with right action, allowing them to speak sentences instead of typing, show the content that they would love to watch, provide them information that they are looking for and so on. Google has processed enormous amounts of data to build models that could recommend content, covert voice to text, parse information from images and videos and much more.
Google is opening its treasure trove of tools, frameworks, libraries for data processing to the customers to innovate. For GCP cloud data processing ecosystem is one of the key differentiators. The research and development from strong team of scientist and engineers at Google is invaluable.
What google offers to innovators this day, is a platform where they can focus on solving business problem and providing value to their customer and let google handle the engineering challenges. There are variety of products in GCP that are available for the customers. Google Cloud Storage, DataProc, BigTable, BigQuery, DataFlow, DataStore, Pub/Sub, ML Engine, Cloud Spanner and AutoML.
