Business Analytics (BA) is the process of applying a range of advanced analytic methods to obtain meaningful insights on why something has happened and what to expect in the feature. For INESIS, Business Analytics is the “art” of extracting and transforming information hidden in data, into knowledge. The era of Big Data has accelerated the use of Business Analytics. INESIS can harness huge amounts of structured and unstructured data and uncover hidden patterns, trends and insights to:
- facilitate companies in improving and automating their business processes
- provide support to organizations for making decisions and gradually automate decision making
At INESIS we consider that for the implementation of successful Business Analytics, close collaboration with our client is necessary. For us communication with business people is very important not only for setting up the initial objectives but also for the collection of valuable feedback during project execution.
No matter where your company stands in the Business Analytics lifecycle, INESIS offers a variety of BA solutions from which you can gain insights that will help you explain why specific results occur, assess previous decisions and predict future events.
Our Business Analytics solutions can be classified into the following high-level categories. Although each type of analytics can be performed in a separate distinct step, our philosophy is that unified approach, consisting of a combination of different types of analytics and methods, is the optimal approach for deriving best decisions in the business lifecycle.
Descriptive analytics looks at the data in order to answer the question “What is happening?”.
In this initial phase data processing, data aggregation and data mining techniques are used in order to organize the data and understand the content and quality. This phase can help you answer questions concerning your business such as the main characteristics of your customers, explore behaviours by specific characteristics such as age or assess the effectiveness of a marketing campaign and make it possible to identify patterns and relationships that otherwise would not be apparent.
Diagnostic analytics answers the question “Why did it happen?”. This means digging into the data to understand the causes of events and behaviours and obtain a deep insight into a certain problem.
INESIS utilizes advanced analytics techniques such as data mining, correlations, segmentation analytics and more in order to help you understand your data faster and answer critical workforce questions.
Predictive analytics focuses on answering the question “What is likely to happen?”.
The accelerating availability of data is coupled nowadays with the widespread adoption of predictive analytics. Predictive and time series analytics concern advanced and complicated statistical or non-statistical techniques, which are applied to both current and historical data in order to predict future events. Predictive analytics find applications in almost all industries of socio-economic life but most often predictions and time series analysis are applied in banking and finance, retail, healthcare, sales, marketing, tourism/travelling and technology sector.
The purpose of prescriptive analytics is to answer the question “What should I do about it?”. This involves suggesting to your business decision-making options on how to take advantage of a future opportunity or deal with a future risk. Prescriptive analytics indicates what the best scheme of actions is through which intended goals can be achieved. This type of analytics considers the outcomes of predictive analytics and business rules for determining both the actions necessary to achieve predicted outcomes, and the interrelated effects of each decision.