Torture the data, and it will confess to anything.
scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured similar to data mining.
Data science is a multidisciplinary blend of data inference, algorithmm development, and technology in order to solve analytically complex problems.
Discovery, Data Preparation, Model planning, model Building, operationalize, communicate results.
Data Science is primarily used to make decisions and predictions making use of predictive causal analytics, prescriptive analytics.
|1. Traditional business applications have always been very complicated and expensive.||1. Data Science removes duplicate informations from data sets and hence saves large amount of memory space. This decreases cost to the company.|
|2. The amount and variety of hardware and software required to run them are daunting.||2. Data Science it is suitable for enormous amount of data. it is used to reduce duplicate data and helps in optimization.|
|3. You need a whole team of experts to install, configure, test, run, secure, and update them.||3. Men power will be reduced and it is cost effective.|
|4. When you multiply this effort across dozens or hundreds of apps, it’s easy to see why the biggest companies with the best IT departments aren’t getting the apps they need.||4. Data Science is Easy to use, configure and install.|
|5. Small and midsize businesses don’t stand a chance.||5. Data Science operations include data extraction, data profiling, data cleansing and data deduping .|
ophel computing Believes Outsiders often have an insight that an insider doesn't quite have.