The global economy: markets and flows of goods are moving and changing at a breathtaking pace. There is an abundance of information, market data and indicators. This is why the ability of companies to draw the right conclusions from the multitude of data and act in real time is becoming a real competitive advantage. The trend towards real-time analysis and decision-making now plays a central role in the modern business intelligence landscape. Technological advances such as the IoT (Internet of Things), cloud computing and modern data management platforms make this possible. New methods such as ELT (Extract, Load, Transform), which is used in the implementation of data lakes, help data scientists to immediately identify errors and derive reliable developments and trends. Collecting, analyzing and presenting relevant business data is of great importance because it enables well-founded decisions, increases efficiency and creates competitive advantages. With business intelligence, you have accurate, up-to-date information at your fingertips to improve decision-making and optimize your business processes. As an IT consultancy that is independent of manufacturers and financial markets, we work with you to evaluate the right business intelligence solutions for you. No matter what your requirements are: We carry out extensions to standard software through to the creation of customized solutions. Our strength lies in taking a holistic view of customer-related analysis and reporting processes and effectively transferring and mapping them in the appropriate BI systems.
Business Intelligence
Business Intelligence - Experience & modern BI solutions
We combine classic business intelligence approaches with modern data science approaches
Traditional reporting, classically located in the data warehouse, is more of a retrospective process. The IT department is responsible for this. It collects historical data, fixed key figures and hard facts periodically from the source data and evaluates them according to clear specifications for classic company reporting. The result: companies use OLAP (Online Analytical Processing) to make quick and accurate decisions along predefined evaluation paths, also known as dimensions.
However, modern business intelligence solutions and decision support systems make it possible to optimize these processes and react flexibly to changes.
While reporting serves to make complicated key facts visible, data and business analyses rely on a direct, event-based evaluation of as broad a database as possible, which also includes metadata in order to identify trends and derive forecasts. Both reporting and data science are used to make decisions based on the reports, forecasts and big data analyses presented and support companies in various ways to improve operational efficiency and thus their added value. This also promotes the effectiveness of process management and the process mining software used, for example.
However, reporting alone is often no longer enough in today’s dynamic economy, which is characterized by technological upheavals such as artificial intelligence. Cloud-supported real-time analyses enable companies to analyze information directly as soon as it is available. This allows business processes to be monitored and quick decisions to be made, paving the way for an agile and adaptive business strategy. And this in turn creates a considerable advantage for company managers: In future, modern business intelligence solutions will enable them to identify undesirable developments, exploit opportunities and avoid risks.
With our customized IT consulting, you can optimize your business intelligence strategy with a combination of classic business intelligence approaches and state-of-the-art data science approaches – and thus create the strategic basis for the successful future of your company.
Business intelligence: establishing your modern data lake strategy
Companies now have a wide variety of systems, some with huge volumes of data. With the trend of no longer operating systems in-house but using an application service provider, the heterogeneity of data continues to increase. In addition, users are demanding ever more sophisticated analyses of ever larger volumes of data. Companies are therefore well advised to establish a data culture and a central data platform including a data lake.
In this way, both structured and unstructured data can be processed and reliably evaluated: While a company’s operational systems maintain core processes in a regulated and stable area that provides very stable and automated processes, the systems provide information and data from a wide variety of source systems, ideally event-based.
Using data lakes, the ELT method and the appropriate analysis tools, simulations or even forecasts can be created very flexibly, almost in real time.
For the successful development of such agile business intelligence architectures, it is essential to collect the data on a use case basis and then make it available for flexible use.
The challenge here is to logically decouple the central data storage in the company’s own data store from the actual evaluations without losing sight of the users.
For example, it is important to differentiate between which reports and forecasts a Chief Data Officer needs and which data is relevant for a data scientist or business user.
The key to business intelligence with real-time analyses: the extract-load-transform process
Extract Load Transform (ELT) is a modern data processing method that is becoming increasingly important, particularly in the course of preparing and structuring data for business intelligence scenarios and data analytics. Especially with the increasing spread of tools such as Google Dataflow, Cloud Storage, BigQuery, Azure Synapse, AWS S3, Redshift, etc., sometimes combined with Snowflake or Databricks, ELT is becoming increasingly important. Using ELT, the data is first loaded into the target data system or a data lake, where it is collected, cleansed, supplemented and only then transformed. This more error-tolerant approach uses the powerful computing capacities and modern data catalog systems and enables fast and agile processing of large volumes of data. ELT is particularly efficient in cloud-based environments, which are characterized by high scalability and flexibility.
Companies are therefore increasingly extracting raw data from various sources, which they obtain externally from their own core system, but also from their application service providers via previously defined service level agreements and load into a designated staging layer, such as a data lake or data warehouse. Once there, they are transformed into meaningful information in the so-called evaluation layer.
The ELT process: an overview of the steps in the data analysis method
The extract-load-transform process is therefore based on three steps, which we will briefly describe again here:
1. extract (extract):
The raw data records to be processed are initially obtained from the entire IT landscape and via loosely connected systems. These are usually integrated on the basis of predefined interfaces, contracts and service levels. If personal data is extracted, it can be masked in compliance with data protection regulations.
2. load:
In order to transform the acquired data quickly, it is loaded directly into an in-house, usually relational structure, if necessary with the help of a master data management system. This reduces the time between extraction and delivery enormously.
3. transform:
The data is made available in the output layer in the form of reports and forecasts according to relevant use cases.
Data scientists can flexibly analyze the raw data or the already processed data.
Although storing such large amounts of data is time-consuming, business intelligence evaluations generated in this way can be called up in real time. This distinguishes such forecasts and evaluations from time-controlled reporting from conventional data warehouses. In the output layer, large volumes of data can be transferred directly to an end-user tool for analysis using in-memory technology.
The advantages of Business Intelligence with Extract-Load-Transform process
The benefits of the ELT process for your BI strategy include:
- Fault tolerance: ELT enables robust and fault-tolerant data processing.
- Powerful computing capacities: The use of modern data catalog systems enables fast processing of large volumes of data.
- Agility: The process is flexible and enables rapid adaptation to changing data requirements.
- Efficiency in cloud environments: ELT makes optimum use of the scalability and flexibility of cloud computing.
- Improved data preparation: Data is only cleansed and supplemented after loading, which improves data quality.
Use our IT consulting services to realize these advantages in your BI strategy and optimally position your company strategically.
Our business intelligence expertise - your competitive advantage
Whichever business intelligence scenario you choose: We develop BI solutions based on the business process.
Our BI experts always focus on the question of “what for” in order to cover your individual requirements in the best possible way. This is because powerful analysis and reporting systems integrate seamlessly into the user’s working environment.
Many business intelligence systems fail to gain company-wide acceptance as certain departments or specialist employee groups are often left out.
Modern BI systems enable specially prepared evaluations and “views” and the necessary data integration for all relevant stakeholders in the company, such as CEOs, CDOs, business analysts, AI developers, data scientists or users of the company’s internal CRM system. They are all dependent on individual information and therefore all benefit equally from the single source of truth approach. Modern business intelligence solutions provide information where information, forecasts and reports are needed and are self-explanatory and intuitive to use in the front end. The right amount of information is always crucial: user-specific filters adapt dynamically to the required content.
However, information alone is not enough: making decisions or deriving the necessary measures can be supported by modern IT landscapes.
Our business intelligence experts make your data clearly accessible – on request using specially developed information and analysis cockpits or printable reports, which we tailor to the requirements of the respective users and stakeholders in your organization. Forecasts and scenarios based on the latest data provide important insights for portfolio analysis or reliable risk management, for example.
Business analytics: the efficient handling of data needs to be learned
Data forms the basis for business decisions and is therefore of central importance.
However, more data does not automatically mean more information – and the volume of data is growing exponentially as digitalization progresses. As a result, companies are now dealing with very large volumes of data. This data is often complex and heterogeneous in terms of its structure, composition and quality, making it almost impossible to process and utilize using conventional methods.
The volumes of data generated by the Internet of Things alone can hardly be processed effectively using a conventional data warehouse.
In this context, it is important to establish modern data lake strategies, efficient data management and a clear data governance structure as part of business intelligence in order to maintain an overview and be able to make reliable statements about which data originates where and which of it is important at all. A fundamental problem for many companies in this context is the lack of a standardized database. The result: those responsible make decisions based on data that is only of limited value. In the worst case, such decisions can jeopardize a company’s business success.
As part of a Statista analysis, we have identified the biggest hurdles that companies face when it comes to using their data effectively. We are happy to support you in optimizing your data processing in order to exploit the full potential of your data.
Our multifaceted business intelligence service portfolio
In addition to a process-oriented requirements analysis, we design and implement company-wide data warehouse and modern BI solutions that enable real-time analyses using agile data lake strategies. We also advise you in detail on data governance, IT and data strategy and work with you to define the necessary role concepts, which are of central importance in many business intelligence scenarios.
Our BI experts are characterized by a high level of technical expertise and many years of experience. We support you from data integration (ETL, ELT, data mesh) to aggregation and presentation in the form of reports, forecasts or dashboards. We are happy to support you in selecting the right tools and also provide suitable user training as part of a rollout. But even after a business intelligence project, we won’t leave you on your own – we’ll be happy to provide you with full user and system support.
Our big data analytics and business intelligence services
Our experienced experts support you in numerous BI areas – from customized design for your effective data analysis and data evaluation to implementation and long-term support.
- Requirement analysis
- Concept
- Flexible individual solutions
- Integration into operational systems/enterprise data warehouse/data lake/data mesh
- Cloud-based BI solutions
- Multi-country solutions
- Authorization management at national/international level
- Data governance, IT security and data protection
- Realization
- Performance optimization
- ETL,
- Data Lake Strategy (ELT)
- OLAP, Data Vault, E-R
- Event-based real-time forecasts
- Key Performance Indicator
- Easy-to-use, user-oriented dashboard/portal solution
- Reporting
- Rollout
- User training
- Support
Would you like advice on how you can use innovative BI solutions such as modern data analysis methods to bring your business analytics up to date?
Then get in touch now – together we can shape your business intelligence.
Proven and powerful business intelligence tools
When you work with PTA IT-Beratung, you benefit from the use of versatile, powerful BI tools:
- ProClarity
- Microsoft Reporting Services
- Microsoft Integration Services
- Talend Data Fabric
- Confluent, Apache Kafka
- Seeburger
- Mulesoft
- Microsoft Analysis Services
- Microsoft Synapse, Data Factory
- Snowflake Data Cloud
- Google Data Cloud
- Microsoft Power BI
- MS Excel
- Excel Calculation Services
- Business Objects
- Tableau
- BEx Report Designer
- BEx Analyzer
- SAP BW Portal
- SAS Data Integration
- SAS Visual Analytics
Our team consists of experienced business intelligence experts who are well-versed in the use of these tried-and-tested tools and can help you find the optimum solution for your business objectives.
Research in our IT projects in the area of Business Intelligence
Anchor a holistic BI strategy in your company with our wide-ranging business intelligence expertise. This forms a solid and indispensable basis for successful and company-wide data analytics projects. Together, we take into account all the steps involved in such a strategy – from data management, analysis and evaluation using suitable BI tools to clear visualization using meaningful dashboards.
Would you like to get an initial overview of our project successes? In our project database you will find a selection of meaningful business intelligence projects:
Important questions about Business Intelligence
What is Business Intelligence, why is it so important for companies today and what advantages does it bring?
Business intelligence (BI) comprises technologies for collecting, analyzing and presenting business data.
Its relevance is based on the fact that it enables well-founded decisions to be made, efficiency to be increased and competitive advantages to be created.
Business intelligence provides accurate, up-to-date information, thereby improving decision-making and optimizing business processes.
BI also enables in-depth data analysis and helps to identify trends and patterns.
These are crucial for business, as they enable companies to react more quickly to changes in the market.
How does business intelligence support strategic planning in companies?
Business intelligence supports strategic planning by providing data-based forecasts and insights into business trends.
Comprehensive data analyses identify market opportunities, manage risks more efficiently and support well-founded, long-term decisions.
BI systems make it possible to simulate various scenarios and evaluate their potential impact.
This enables companies to react proactively and flexibly to changes.
What role do data analysis companies play in the implementation of business intelligence solutions?
Data analysis companies are crucial for the implementation of business intelligence solutions: They integrate data, carry out analyses and support the introduction of BI systems.
Their expertise ensures efficient implementation and maximum benefits for customers.
They also provide employee training to ensure that the new BI tools are used effectively.
This enables companies to exploit the full potential of their business intelligence investments.
Our business intelligence services – your strategic advantage
Customized business intelligence consulting is part of our comprehensive IT services.
Our expertise in data analysis and integration enables us to develop individual strategies that are precisely tailored to your needs.
With our in-depth business intelligence consulting, we help you to use your data efficiently – increasing your competitiveness.
Rely on our many years of experience and in-depth knowledge in the field of business intelligence to help you achieve your business goals.
For more information, please contact us.
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