Data Science has become a popular subject opening a fresh array of possibilities for upcoming data engineers and scientists. Business Intelligence is a derivative of data modernization => turning raw data into an asset, thus increasing its utility in 2020 and beyond. It is the fastest way to achieve Artificial Intelligence-driven modernization to source all the data that matters to the business and deliver enterprise-wide intelligence. It transforms data into an asset.
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Although programming packages that make it easier to make machine learning models are available, it’s still pretty important to understand a lot of computer science that underlines this scenario. It might as well require quite a bit of training, especially for folks who don’t have any experience in computational thinking.
Concepts that go in favor of the current context: Data Modernization => Modernization Method and Modernization Platform:
Data Modernization allows leaders to leverage data as an asset to the enterprise and helps drive revenue, growth, contain costs and strengthens corporate valuations by:
From applications in smartphones (voice assistants: Apple’s Siri, Google Assistant, Amazon’s Alexa, Google Duplex, Microsoft’s Cortana and Samsung’s Bixby; app store and play store recommendations; face unlock), transportation optimization (dynamic pricing), popular web services (e-mail filtering, Google Search, Google Translate, LinkedIn and Facebook Recommendations) Sales and marketing (Recommendation Engines, personalized marketing, chat support queries/chatbots), security (video surveillance, cybersecurity captchas, speech-to-text model)), financial domain and other popular use cases – machines can be used to automate just about any of the everyday tasks.
Data Science is primarily used to convert meaningful data into marketing and business strategies that help a company grow. It has spanned across various business sectors including e-commerce, health-care, finance, education, shipping, logistics, etc. Tools that make it even better: Hadoop, R programming, SAS, SQL, etc.
Besides these, one of the most popular tools in Big Data Real-Time Analytics is Python. It supports structured programming, object-oriented programming, and functional programming approaches.
All these stages are applicable only to text data. If such data comes in the form of images, then some different best python frameworks and libraries can be used for image processing. Konstant has been engaged in delivering apps with faster delivery times, at a reduced total cost of data. We can deploy at earliest (even within a month’s timeline) realizing the value within six months. We empower real-time, enterprise-wide analytics and intelligence web application development services to re-invent, re-engineer and augment data platforms of your choice. Get a word from our developers to network, learn and improve!
Neeti got her master's degree in software engineering in 2009 and has been working since for software companies of all sizes as a technical writer. What started as a high school passion has now been converted into a serious profession. She has a special knack of learning from all verticals and imbibing the extracts into her writing. She enjoys learning technical aspects of writing from her tasks where her experience and understanding are most impactful.