IT consulting
Big data: solutions for volume, variety and speed
Many companies have been analyzing external and internal data extensively for a long time. However, additional technology must be used in many areas to overcome the challenges posed by large and rapidly changing, often polystructured data volumes. This is because big data does not just mean a different dimension of data volumes, but big data stands for:
- Volume: Enormous amounts of data require scalable systems
- Variety: Different data formats must be integrated
- Velocity (speed): Real-time analyses are crucial
Volume: The exponential growth of data
According to Wikipedia, the global data volume amounted to 60 zettabytes (60 trillion gigabytes) in 2020 and is growing by 25% every year. This huge amount of data could form a stack of Blu-ray discs that exceeds the weight of the Giza pyramid.
While social media data such as from Facebook and Twitter is often cited as an example of big data, the more relevant information is usually found in internal and external data sources. However, detailing, combining and historicizing this data often leads to volumes that are difficult to manage. The segmentation, partitioning and prioritization of data sets is therefore crucial.
Industry 4.0 and the Internet of Things (IoT) are further increasing data growth and presenting companies with major challenges.
Challenges for companies:
- Handling large amounts of data
- Efficient data organization
- Integration of new technologies
Diversity: Dynamics and flexibility in data processing
The multitude of technical solutions, globalization and rapid system changes lead to constantly changing sources of information. Relational databases expect pre-structured data, while big data solutions are flexible and only structure data during analysis (ELT instead of ETL). Modern databases process formats such as JSON using NoSQL modes, often without introducing new technologies.
Challenges for companies:
- Integration and adaptation to changing data sources and formats
- Flexibility in structuring and processing data
- Efficient use of existing databases and technologies
Companies need to react flexibly to dynamic data sources and make optimum use of existing systems in order to manage the diversity of big data effectively.
Velocity: Fast decisions through big data
Big data analyses provide valuable insights within seconds, for example on investments, target groups or process optimization. However, traditional data warehouse systems quickly reach their limits when it comes to handling large volumes of data. A combination of traditional, main memory-based and batch-processing systems can overcome this challenge. At the same time, it is crucial to focus on relevant information in order to ensure efficiency.
Challenges for companies:
- Processing and analyzing large amounts of data in real time.
- Integration of new technologies with existing systems.
- Focus on the essential and relevant information.
Companies need to optimize existing systems, integrate real-time solutions and focus on relevant data in order to use speed as a competitive advantage.
Use the potential of big data
Processing large and complex volumes of data is one of the key challenges of digital transformation. Companies are faced with the task of efficiently managing enormous volumes of data, integrating a wide variety of data formats and enabling real-time analyses at the same time.
This is exactly where our consulting services come in: We are happy to conduct feasibility studies and free consultations with you on the subject of Big Data and related topics. In this way, you can ensure that the benefits of your planned solution are safeguarded.
We make the methods and potential of big data and AI tangible – e.g. through potential workshops or proof-of-concepts.
We support you in the conception of your projects – from brainstorming using design thinking, through the structured development of a use case , to the prototype and the fully automated processes.
We accompany or take over projects from start to finish – from prototyping and technical conception to project management – and also optimize existing systems, as well as improving your BI and AI systems both technically and methodically.
- Hadoop
- Impala
- Oracle Exadata
- IBM Watson
- Talend ETL
- Kafka
- Apache Drill
- Hive
- Parquet
- Spark (in certain contexts also as a method)
Discover your potential!
We help you to use data volumes efficiently. With big data technologiessuch as distributed systems, real-time analyses and AI, you gain insights, optimize processes and make well-founded decisions – scalable and future-proof.
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