What is Data Analytics: How can it help you?
Data analytics is the science facilitating data collected from IoT devices, business transactions and any customer interactions to make sound business and technical decisions. The data includes ambient temperature, battery life, and IoT device usage patterns. e.g. smart locks, temperature sensors etc. Data Analytics is the technology facilitating raw data processing and providing meaningful information.
Thus, we can say that Data analytics explores and analyses the extensive accumulated data to find trends and valuable insights for business and technology development.
Why do businesses need Data Analytics?
Data analytics allows businesses to make strategic decisions such as productivity, and marketing campaigns, adapt quickly to market trends and stay ahead of the competition in today’s fiercely competitive global markets. Simply put, it can be used to make predictions based on historical data.
The use of data analytics in access control systems, such as the one from Xiotec Limited, will facilitate, e.g. role-based access to offices and apartments using the smartphone. This is not possible with mechanical keys.
How does data analytics work?
Data analytics involves the following steps:
Identification:
Data analytics starts with identifying the problem/issues requiring attention.
Data collection:
The data is collected from various relevant resources. The data can be collected from internal resources such as software logs, ERP systems, CRM software, marketing systems, etc. The data can also be collected from external sources such as google maps, internet search engines, etc. The data collected is then appropriately organised so it can be used for analysis using tools such as a spreadsheet or any other software.
Cleaning:
The data is cleaned up by removing duplicate information and unwanted data points, correcting any errors and filling up gaps in data, etc.
Analysing:
The data is then analysed using analytic tools/software to find meaningful information. The data analytics techniques may use artificial intelligence, simulation, machine learning algorithms, automated tools, and systems.
Interpretation:
The analysed data is presented to the user in various forms to interpret the results. The user looks at the information to identify the issues or extract requisite details.
Data Analytics Types
The four basic types of data analytics are:
Descriptive Analytics
Descriptive Analytics identifies the past instances. For example, a company may examine sales trends of its products for the last few years to predict future sales strategies.
Diagnostic Analytics
Diagnostic analytics tries to understand the occurrence of a particular event. It tries to diagnose a problem just like a doctor tries to diagnose a disease by looking at a patient’s symptoms. For example, finding the factors impacting sales of a particular product or instrument.
Predictive Analytics
The predictive analysis provides information about future trends based on historical data. Businesses use predictive analysis to forecast future growth. With new tools and techniques available, predictive analysis is also used to predict trends based on various events. For example, retailers determine seasonal trends and optimise inventory.
Prescriptive Analytics
Prescriptive analytics provides recommendations for the future. It will enable companies to make informed decisions on new investments in areas of business or new products.
Summary
Data analytics allows us to take informed decisions based on past data to drive strategic and tactical business decisions. The use of data analytics allows intelligent access control solutions to reinforce the security of offices and other shared spaces and improve the access management system’s performance, provide valuable insights and drive revenue.