A proper framework is required to implement these iterations. Several data lake projects fail because they lack operational data flow, self-disciplined users, and appropriate data lake governance. In this blog…
Once organizations have ensured that they have the necessary technology, tools, skill sets and architectural concepts to facilitate a sound data integration roadmap, they need to constantly evaluate market offerings…
A real world example is that of Uber. The business of Uber solely runs on the network of connections. The service is dependent on, among other things, the quality of…
Cities can use an open data framework to tailor it to their specific needs. This can be a city’s infrastructure expansion, making policies or determining the investment levels for technology…
The discipline of data integration comprises the practices, architectural techniques, and tools that ingest, transform, and combine data from several platforms within the enterprise and beyond. Gartner estimates that revenue…
But, along with the advent of new business opportunities, comes the additional costs which are needed to maintain and secure such a massive amount of data. Many companies, especially in…
While the former is a safe full of rich data, the latter is the key to accessing it, intelligently. How are Deep Learning and Big Data related? Public and private…