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How to Achieve ETL Test Automation
Today’s businesses run on data. The challenge, however, is ensuring that the data is in the right form so it can be turned into business intelligence (BI) reports, data-driven strategies, comprehensive analytics, AI, machine learnings and other insights that executives use to make informed decisions.
Integrating Slack into the Test Automation Process
Over the past few years, the use of automation tools to test applications has increased exponentially. Every organization serious about technology development wants to deliver IT projects by employing continuous integration and continuous delivery strategy.
Test Automation Utilizing Docker Technology
To support the fast paced software industry, DevOps and Agile practices have established themselves as a helping hand. With ever increasing large scale digital transformation projects, organizations realize that the only way to shorten the product development cycles is to automate the processes involved in the delivery pipeline.
Monetizing the data in your business
It is no exaggeration that data is the new form of currency today; it’s as much an asset as oil and gold are in today’s economy. It was only in the past decade that many companies realised the potential of right data as invaluable asset to organisation’s growth and performance. And ever since that, organizations have been formulating ways to fuel their business growth through data. Before we move on further, let’s understand how valuable data is for any business.
Implementing DevOps with Containerization
Traditionally, application development, testing, deployment, support (monitoring) were all treated as separate entities, and multiple departments (vendors) were involved in the completion of the software lifecycle. This resulted in a fragmented approach to the process, people, tools, later impacting the final product performance, features, cost, schedules and quality.
Predicting the Art-of-Data-Science
Data science, one of the hottest fields in tech today, has many dimensions and applications. As we all are familiar, in science, we can understand the features, behavior patterns and meaningful sights by formulating reusable and established formulas. Similarly, we can understand the behavior patterns, meaningful sights, through engineering and statistical methods from data as well. Hence, Data science can also be also viewed as Data + science, or the science of data.
IoT fueling Oil & Gas industries
Several Industries including Oil and Gas, Manufacturing, Mining, Healthcare, etc. deploy technicians and machines at remote locations. These technicians operating at the remote locations on the ground need real-time data and guidance with respect to multiple aspects of the machine operational schedule, tool wear and tear, weather forecast, etc. A robust strategy that enables and empowers them with critical data needs is imperative to achieve business success. This will be of real help in providing them with real-time data to mitigate operational risks and challenges in day-to-day activities. This will further improve business preparedness for overall risks and performance.
The World of Data, Warehouse, Lake and Hub
Every organization has enormous amounts of data that needs to be stored and managed. Effective data management is the critical aspect of any organization and the ability to access and communicate the data are the key factors that decide the efficiency in data management. The sheer volume of data that must be managed by organizations has increased so markedly that it is often overwhelming to manage it.