Data warehousing
Approximately 15 years ago, management information solutions (MIS) were very rare in Slovakia, while today we can say that if a company does not have high-quality MIS, it can not compete with companies who already use such system.
MIS is a part of Business Intelligence (BI) which represent a wide class of application programs and technologies for decision-making support. Today, we know many solutions supported by various technologies in the market which belong to MIS and in most cases have one common denominator, data warehouse (DWH).
The issue of data warehouses is no longer something new these days, quite the opposite. Most of the large companies already own data warehouse, or they plan to build it. DWH provides an opportunity to collect, extract, clean, transform, consolidate, and unify data from various information systems, as well as transaction. Quality data warehouse which use so-called Master data management contains a single truth in the company and thus it serves as the base for reporting at all levels of the company.
Master data management
Master data management (MDM) is a method of identifying the most critical information within the organization. It involves a number of technological solutions, data integration, data quality and process management.
Main benefits of MDM:
- unified view of the interpretation of information from multiple data sources
- defining administrative links between data within the business rules
- complete view of all interactions for monitored business entity.
Integration and data consolidation
With an increasing number of data, used applications and systems in companies, it is necessary to consolidate information and edit them in “a comprehensible language”. Therefore, companies are forced to transfer data from their systems to the new environment, which can be complicated, time-consuming, but also costly.
The causes of problems with corporate data:
- using outdated systems, where it is difficult to understand data without special knowledge
- the data in outdated systems are often mutilated by their inconsistency
- applications are no longer supported by manufacturer and a customer cannot use data
- wrong information and typing errors, such as meaningless addresses, names and the like.
These problems can be solved by standardized tools and technologies.
Main benefits of data integration solutions and consolidation:
- reducing time for implementation thanks to the professional approach
- strict monitoring of costs in the project, meeting deadline for implementation and elimination of project risks
- ensuring profiling of data, quality and data structures review
- application of transformation and cleaning mechanisms for removal of inconsistent data between systems, and improvement of the process of organization
- complete documentation of solutions.
Reporting
Management staff use reporting systems for a perfect overview about the current status of the company. Fast access to information is a powerful tool that allows them to consider whether the business is in conformity with the company, and short-term and long-term objectives emanating therefrom.
Through reporting system managerial staff can monitor at different levels the condition of the components or more precisely processes, which they are responsible for. In addition to an easy and simple use, it is essential to have clear and real data.
Our company provides reporting system with simple tools whereby you will be able to monitor and analyze performance of the company. We offer not only technological platform, but we can also help to set up processes so that you can check their performance in accordance with the objectives.
Thanks to our solutions you will get:
- reporting tools whereby managerial staff will be able to communicate more clearly adopted strategy that will make better identification possible
- clear connection between adopted strategy, operations and efficiency of business
- knowledge about different parts of the strategy - the objectives, key indicators, adopted measures and operating performance
- ability to define the link between the causes and consequences
- possibility to map targets of the company, departments, groups and individuals
- unified environment for defining strategic objectives, performance parameters, as well as monitoring and planning of them
- ability to adjust processes of monitoring and checking of the adopted strategy in more detail, its implementation and impact
- connection of the planning process with the adopted strategy up to the operating budget level.
Financial, statutory and management reporting
Financial, statutory and management reporting provide consistent data for correct decision making. It is very important to unify the process of preparation across the organization to all types of reports. You can achieve not only better clarity, transparency and a shorter preparation time, but at the same time, you will be able to approve changes resulting from new requirements of regulatory authorities and/or organization itself.
When preparing reports we are facing these deficiencies:
- errors and inconsistencies caused by manual processing and incongruity of processes in collecting data and preparing reports
- differences in data and results between statutory and managerial reports
- lack of transparency between reports and input data
- lack of reports with higher content of non-financial data
- long preparation of regular monthly/annual reports
- complicated management of report versions
- issues with data preparation based on various regulatory rules
- complicated data collection from a variety of sources.
Forecasting
For companies that want to continue to grow and compete on the market is extremely important work with historical data. Tools and techniques of BI enable better understanding of their potential. Thanks to forecasting (predictions, estimations), it is possible to allocate budgets for the upcoming period, correct plans, and to adapt to a new market situation. A major advantage of BI tools is the link between forecasting, planning and reporting, that maximize the efficiency of work.
Planning
Our BPF solutions enable you to significantly reduce the time required for planning, thanks to the decrease of the manual activities for working with data and the application of transparent procedures related to the preparation of budgets and forecasts.
Planning areas:
- strategic planning
- tactical planning
- financial planning
- management reporting
- forecasting
- risk management.
If you apply our solutions, we guarantee:
- reducing time required for the preparation of plans and budgets, simplifying and speeding up adjustment plans, budgets, and periodic forecasts of development
- maximum auditability of changes in the preparation of plans and budgets
- better control of the planning process by monitoring assumptions that were taken into account in the preparation of plans and budgets
- unification and mutual visual connection between the strategy, financial and operational planning
- creating and design of decision-making processes, budgeting and forecasting future developments.
DATA MINING AND STATISTICAL METHODS
Data mining promoted statistical methods in many ways. There is a strong emphasis on process automation and its results are presented in the form of reporting.
Typical issues addressed by data mining:
- customer segmentation
- detection of fraud and other anomalies
- prediction of customers who will be able to respond positively to the marketing campaign (selling a new product, cross-selling, up-selling, maintaining customer)
- shopping basket analysis (identification of products which are often sold together)
- prediction of time series
We divide statistical methods into two basic categories:
- Descriptive statistical methods describe actual condition and allow better understanding of reality. They use frequency and contingency tables plus data visualization (histograms, pie charts, bar and line charts). They often describe distribution of values by one or more indicators (diameter, median, percentiles, minimum, maximum, standard deviation, etc.). They are represented in reporting and in business intelligence.
- methods of the inference statistics - knowing that getting a complete set of data may not be possible due to demand, time or finance, statistics knows how to work with a random sample data on which it predicts real parameter values. Methods of inference statistics are divided into:
- an estimation of parameters and intervals - use in various surveys
- tests of the hypotheses – allows, for example, to specify effective marketing campaign, test the effectiveness of new medicine, determine the most compelling product packaging or set mix of radius in order to satisfy the target group.
- modeling allows to find relations between the dependent variable and many independent variables. We can model, for example, salary of an employee depending on his age, education, working conditions and years of experience and thus predict salary of the new employee. Another example is the prediction of customers who will buy a new product. It is also possible to model a development of various indicators in time.
Big data
Did you know that every day there has been more than 3 exabytes (1018 bytes) of data and 90% of existing data over the last 2 years? They come from various sources - from meteorological sensors, social networks, mobile phones, GPS, and have various formats (photos, videos, bank records, and many others). They are referred as Big Data.
Big data are defined by the following characteristics:
- Capacity - the amount of data is too large to be processed by traditional applications
- Diversity - they come from various sources and may be structured, semi-structured and unstructured
- Speed - they result from increasing speed
- Variability - number of data fluctuates in time
- Complexity - data can come from various sources and, therefore, data management is more intensive.
Big Data represents tools and technologies that help us to overcome these obstacles.