- Our Mission is to release and enable your data.
- Our Vision is the best way to provide data to a customer.
- Our Values – data quality, accuracy, certainty and predictability.
Business analytics and Business Intelligence (BI) are not the same and one phenomenon in the company. Most likely when a company wants to have daily business reports they must be well done. Processes like today’s sales, tasks performed by employees for this moment, etc. All this can be done with Business Intelligence. Business analytics based on business day-to-day insights can provide excellent results to determine the company’s future. Future activities, create new products, predict market demand, customer preferences, etc.
The need for Business analytics and Business Intelligence
- Effective activities
- Process optimization
- Data quality assurance
- Reduction of operations risks
- Customer knowledge and retention
- Sales grow up
- Validity of decisions
Business analytics and Business Intelligence for effectiveness
Both activities are important in the company. Accelerating the performance of the work faster, more accurately and in a timely manner. It allows you to plan activities forward and review them in retrospect. All you need is to collect your company’s data and turn them into interactive reports. Reports can display insights into your company’s activities in real time, and plan activities for future.
Data quality assurance and reduction of operational risks
When Business Analytics solutions are introduced, as a rule, data quality and quantity are encountered as a rule. If the amount of duplicated data can be tolerated in some cases. Deviations from the quality of the data should be corrected as soon as possible. This is not an easy process, often requiring human resources to ensure better data quality. However, BI tools help you solve this problem in a partially automated way. Data can be cleaned in automated way. Often, until abnormalities are seen in various reports or graphs, the question of data quality does not arise. It is usually suggested that the data be corrected where it is stored at the original source. In case if cleaning can’t be done in source systems it is possible it to clean it during ETL process.
Customer knowledge and sales promotion
These are two very closely related themes of BI and Business Analytics, they are interrailed there, but growing sales without the knowledge of our customers is very difficult. Customer knowledge covers several areas, data collection, storage, legitimate use of data and other topics. Modern BI and Business Analytics solutions already offer how to combine it all. As 90 percent happens, usually when the customer’s cognition subsystem starts to develop, it is that the data is not suitable for full customer cognition. For example, when customer changed his mind for direct marketing or what is customer’s date of birth if it was not collected or the phone number was entered into the ERP system without strict rules.
Some of the problems can be solved by automated ETL processes, which facilitates, not only the provision of highly informative information to sales or customer management departments, but also to the customer himself. For example, if customer information is not properly stored (the address is not stored with classificatory rules) it will be difficult to achieve the goal: ask the customer the same question as little as possible. When we see what our customer likes, when he or she regularly refuses or buys new services, we are recommended by others (by phone, soc. networks etc.), then we can consistently start growing sales. Once both such BI and Business Analytics subsystems are operational, they can be combined in one place and even monitored as sales change when such systems operate in production environment .
Validity of decisions
Often, our decisions are neither logical nor statistical, but flair. It’s not bad, it just as it is. However, it would be very useful to make decisions taken reasonably as possible, e.g. why it makes sense for us to collect some additional customer information, whether it will bring us some tangible benefits, whether we will achieve sales growth for a particular product, etc. So naturally BI and Business Analytics undoubtedly increase the validity of decisions, less encourage decision-making blindly, relying solely on flair.
These were just a few areas where the usefulness of BI and Business Analytics is no longer in doubt and is already fully established in various areas of business. According to forecasts, the BI market is growing from around $23 billion a year (7 percent CAGR) this year, so this is undoubtedly true for many, modern-minded companies. Now it is not even very expensive solutions available even for small or medium-sized enterprises, which can be implemented both in the cloud and locally.