A modern data infrastructure is essential for retailers looking to stay competitive today. Companies are abandoning more traditional, on-premises IT infrastructures and moving to more centralized “as a service” (XaaS) models of delivery enabled by cloud technologies, according to McKinsey. Aging on-premises infrastructures are unable to meet demands for agility and innovation, eating up too much time and too many resources for teams trying to maintain them.

Financial inclusion, defined as the availability and accessibility of financial services to underserved communities, is a critical issue facing the banking industry today. According to the World Bank, 1.7 billion adults around the world do not have access to formal financial services, meaning that they cannot open a bank account or access credit, insurance, or other financial products.

The importance of timely and accurate IT insights is increasing rapidly in the modern era. Organizations often desire a customizable solution to meet the specific needs of their business best and increasingly want to mix data from multiple sources and match data to sales, HR, asset management and other sources in order to better understand root causes and drive better decision-making. To do so, they need a solution that is able to be flexibly tailored for all use cases.

Software testing techniques help us ensure that our software meets all the requirements. The goal of testing techniques is to find out missing requirements, gaps, and errors in comparison to the actual requirements. Finding the right testing technique can be a little challenging. These techniques help us to identify test conditions. Note that there are multiple types of testing. One example is the black box testing technique. In this process, developers test their applications through different inputs.

How to preprocess data using BigQuery ML.

BigQuery BI Engine is a fast, in-memory analysis system for BigQuery currently processing over 2 billion queries per month and growing. BigQuery has its roots in Google's Dremel system and is a data warehouse built with scalability as a goal. On the other hand BI Engine was envisioned with data analysts in mind and focuses on providing value on Gigabyte to sub-Terabyte datasets, with minimal tuning, for real time analytics and BI purposes.

Uncontrolled cloud costs pose an enormous risk for any organization. The longer these costs go ungoverned, the greater your risk. Volatile, unforeseen expenses eat into profits. Budgets become unstable. Waste and inefficiency go unchecked. Making strategic decisions becomes difficult, if not impossible. Uncertainty reigns.

Arvind Fashions Ltd digital transformation unlocks the value of existing applications, new insights, and build solid workflow through Google Cloud.

The role of the CDO will not suffer the slow rise to prominence other emerging C-level roles have seen in previous years. Modern technologies designed to easily centralize, access, analyze, share, and monetize data have arrived. As a result, data has become the most powerful resource to drive an organization’s transformation. That puts CDOs at the wheel, their foot on the pedal, and their fellow execs holding on tight for the ride of their lives.

Lytics leverages Google BigQuery to offer data infrastructure as a service, and Google Cloud AI/ML stack to identify and create unique audience segments.