Reporting and Visualizations
Studies show that one of the most fundamental ways to help people today cope with information overload is to visualize it. In layman’s terms, this means drawing it out as a graph, plotting it on a map or even using data to create an interactive diagram.
By mapping out data visually, it is not only easier to digest and understand important information, it is easier to discover key patterns, significant trends and compelling correlations which may have otherwise been challenging to unveil. Bottom line: you don’t just understand what’s happening, you understand why.
Data integration is the process of combining data from different sources into a single, unified view. Integration begins with the ingestion process, and includes steps such as cleansing, ETL mapping, and transformation. Data integration ultimately enables analytics tools to produce effective, actionable business intelligence.
When a company takes measures to integrate its data properly, it cuts down significantly on the time it takes to prepare and analyze that data. The automation of unified views cuts out the need for manually gathering data, and employees no longer need to build connections from scratch whenever they need to run a report or build an application. Additionally, using the right tools, rather than hand-coding the integration, returns even more time (and resources overall) to the dev team. All the time saved on these tasks can be put to other, better uses, with more hours earmarked for analysis and execution to make an organization more productive and competitive.
Data Science, Artificial Intelligence, Machine Learning
Put simply, data science refers to the process of extraction of useful insights from data. This interdisciplinary approach merges various fields of computer science, scientific processes and methods, and statistics in order to extract data in automated ways. In machine learning (ML), statistical methods are used to empower machines to learn without being programmed explicitly.
(AI) Though it’s a broad term, at its core, artificial intelligence (AI) refers to the process of making machines enable to simulate the human brain function. In the modern technology landscape, artificial intelligence is divided into two key areas. The first one is general AI, which is based on the concept that a system can handle tasks like speaking and translating, recognizing sounds and objects, performing business or social transactions etc. The other one is applied AI that refers to concepts like self-driving cars.