Big Data Solutions

Enterprises and organizations have vast amounts of data at their disposal. With these, developments can be forecast, measures taken and processes improved – if organizations succeed in processing, filtering and evaluating them!

CONET supports customers in determining strategic goals and measures for their data management and in identifying and integrating the right tools. With the targeted processing, analysis and reporting you can draw the correct conclusions and take suitable measures for your ongoing business success.

At the CONET company’s founding more than 30 years ago, our first motto was: "We transform your data into information“. This motto could hardly be more relevant today. More than ever it is essential to filter and evaluate valuable information from the omnipresent data flood in order to identify valuable approaches for your own work.

Illustration CONET: Big Data - Data Handling Strategy

Big Data - Data Handling Strategy

Exemplary Big Data Scenarios from CONET’s Project Work

  • Data Base Infrastructure:

    As an in-memory database, SAP HANA enables the administration and real-time processing of significantly larger amounts of data than has been possible with traditional database systems. In the best sense of a continuous business intelligence, traffic or weather data can be integrated in real-time into your logistics processes in order to e. g. provide enough refrigeration aggregates in case of a delivery of perishable goods or to help you to optimize your production and supply chain as well as your merchandise and storage management across all sectors by providing reliable and flexible forecasts and analyses.
     

  • Data and Information Integration:
    For several years, contact centers have played a leading role in processing and providing customer data. Submitted orders, previous contacts and the customers’ actions on your website have long been established information sources for marketing and distribution purposes. Numerous sensors in products and devices which partly transfer data automatically deliver further insights regarding market analysis, sales planning and technical support which also have to be recorded, evaluated and integrated into the customer care processes.
     
  • Communication and Data Streams:
    Control centers in civil protection and disaster control or control rooms like the command centers of energy suppliers receive valuable additional information through the direct integration of geographical and traffic data, social media news and sensor data from traffic management systems and smart grids. On such an extended knowledge base they can react and decide faster and more reliably.

Myriads of Data – but Where is the Important Information?

The continuing digitalization and the increasing interlinking of our business and social world summarized under keywords such as Internet of Things (IoT) and Industry 4.0 generate an apparently untameable data flood: From the spacecraft to the domestic refrigerator, more and more sensors are installed. Devices and machines from smartphones to cars incessantly collect new data. Already in 2011 analysts at IDC and the journal CIO predicted that the data volume collected worldwide would duplicate every two years with this figure set to increase in future.

In fact, these data treasures often remain unused or insufficiently used. The paradox in this situation is: the larger the data amounts, the higher is their potential – but the more difficult it becomes to extract the relevant and useful information from them. This is why the phrasing of “data mining” has been coined as a term for this „information treasure hunt”.

Often even the right approach is lacking – which information sources and data are really relevant, how shall these be registered and processed and how can added values be made tangible and realized? CONET can assist you with a structured approach, in which - first of all - potential use cases are identified, manageable pilot projects assisted and from this further suitable steps derived to manage the apparent data chaos.

Illustration CONET: Big Data -  Data Handling Process

Big Data - Data Handling Process

Technical Complexity Due to Missing Structure

Apart from the vast data amounts, the diversity of the data recorded is posing a core technical challenge: Their missing structure as well as the numerous different file formats bring traditional business intelligence systems to their limits.

Traditional data warehouse solutions are based upon the administration of structured and unified data, which have been generated via complex extraction, transaction and loading processes (ETL). Considering today’s unstructured data amounts, such procedures are no longer suitable for efficient data handling.

Predictive Analytics – Using Data as a Competitive Advantage

New approaches help to record data efficiently, e. g. via cloud infrastructures, to store and process them in a data protection compliant way, to display them in just the right moment or to integrate them into existing processes – including classifying and categorizing them with suitable processing power, evaluating them automatically by using data mining and machine learning, making them available in real-time for stationary or mobile use and thus having them finally ready as your important basis for making decisions. Only then will they be suitable for predictive analytics which in turn will allow you to transform analyses and trends into faster and more reliable forecasts and to implement the necessary measures to advance your business.

Trust in CONET’s big data expertise! On the basis of our long-standing experience in the storage, administration and processing of data streams, business analytics and business intelligence as well as in the integration of information systems into business processes and business applications, we are your ideal partner for big data management and big data analytics.

We transform your data into information!

Related Solutions

Technologies

Foto: Director IT Infrastructure Hardy HeynenXingXing Unternehmensprofil
Foto: Managing Consultant<br>Business Development Mathias Bründer