Data Analytics
What do we mean by Data Analytics?
Have you ever wondered where does Data Analytics stand in the vast realm of IT? To put it simply, DA is the mechanism of studying data sets in order to draw conclusions and find trends in any information they possess. Furthermore, data analytics is performed with the support of specialized software and systems.
Data Analytics techniques and technologies are largely used in commercial industries to allow organizations to make more business-friendly decisions. Researchers and scientists use data analytics tools to accept and reject scientific models, hypotheses, and theories.
Real-Time Dashboards
Dashboards to monitor real-time business events and to evaluate Key Performance Indicators (KPIs). Publish relevant information to stakeholders Read More
Intelligent Reporting
Information routing to relevant stakeholders with business forecasts for proactive planning, business management and policy making Read More
Intelligent Reporting
Information routing to relevant stakeholders with business forecasts for proactive planning, business management and policy making Read More
Exploratory Data Analysis
Discover underlying patterns in the data, visualize key correlations and make graphical representation to communicate better Read More
Anomaly Detection
Detect what can go wrong in near future, flag suspicious transactions and assess which equipment is breaking normal operating values Read More
Anomaly Detection
Detect what can go wrong in near future, flag suspicious transactions and assess which equipment is breaking normal operating values Read More
Data Mining
Retrieve information from unstructured raw data, develop automated workflows to discover behaviors and make recommendations Read More
Statistical Analysis
Cluster similar customers and study characteristics, forecast demand & supply, and develop A/B testing to find top performing assets Read More
Statistical Analysis
Cluster similar customers and study characteristics, forecast demand & supply, and develop A/B testing to find top performing assets Read More
Data Analytics Roles and Types
Data Analytics services Australia and techniques involve confirmatory data analysis (CDA) and exploratory data analysis (EDA). EDA plans to find relationships and patterns in data; on the other hand, CDA implements statistical methodologies to figure out if the hypotheses of data sets are true or false. Given this process, data analytics can be categorized into two types:
- Quantitative Data Analysis
- Qualitative Data Analysis
Quantitative Data Analysis includes quantifiable variables with numerical data. These variables can be measured and compared statistically. Meanwhile, the qualitative one tends to be interpretive; it focuses on the content of non-numerical data like images, text, audio, and video, as well as themes, phrases, and points of view that are definitely helpful in the cases of data analytics consulting services.
Some advanced Data Analytics types are the following:
- Data Mining
- Predictive Analytics
- Machine Learning
- Text Mining
Data Analytics versus Data Science
With the rise of automation, more focus will be on business needs, deep learning, and strategic oversight. Data Analytics will focus on routine tasks and model creation in business intelligence. Data scientists are more focused on the production of broad insights. There should be no as such comparison between data analytics and data science as both are equally important.
Futuristech and Data Analytics
Data Analytics is the domain that deals with studying vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions. Our Tech savvy engineers at FuturisTech use data Analytics end-to-end pipeline extract insights using business logic & machine learning and deliver insights in dashboard and or reporting tools.
Data Analytics Australia has more roles to play than we would initially like to imagine and it is as important as Data Science now and in the future endeavors of information technology and different computational tasks. It is good to have a grasp on Data Analytics for the best.
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