Data growth & data economy: opportunities and challenges
According to international market research institute IDC, the amount of data produced worldwide will rise from 64 zettabytes in 2020 to around 175 zettabytes in 2025. By way of classification: 1 zettabyte corresponds to 1 trillion bytes or 1 billion terabytes.
From an economic perspective, the use of data creates enormous opportunities. The Federation of German Industries (BDI) estimates the value-added potential of the data economy by 2025 at up to 425 billion euros for Germany alone and up to 1.25 trillion euros for the whole of Europe.
Data is a key factor in competition and value creation as well as a driver of innovation in the economy. Among other things, they can help make better-informed business decisions, optimize processes or develop completely new business models.
At the same time, handling data is a major challenge for all stakeholders. This applies in particular to SMEs, which must have technical and organizational expertise in order to benefit from the diverse value-added potential of the data economy.
It is therefore important to have a robust and reliable platform for managing and analyzing large amounts of data. Delta Lake is one such platform. In this article, we would like to introduce you to Delta Lake in more detail and discuss the various possible uses.
What is Delta Lake?
Delta Lake is an open-source storage framework that allows you to build a lakehouse architecture using compute engines such as Spark, PrestoDB, Flink, Trino, and Hive. It provides APIs for Scala, Java, Rust, Ruby, and Python.
Delta Lake provides a solution that combines the benefits of data warehousing, data lakes, and streaming, with features such as ACID transactions, versioning, and unified batch and streaming processing. Delta Lake runs both on local servers and in the cloud and offers a wide range of features needed to manage big data.
Why Delta Lake Benefits at a glance
Transactional integrity
Delta Lake provides transactional integrity for big data. This means that the data in Delta Lake supports atomic ACID transactions, ensuring consistency and isolation. This feature enables developers to execute complex ETL processes securely and reliably. Transactional integrity can prevent erroneous or inconsistent data, which in turn enables reliable and accurate analyses.
Scalability and performance
Delta Lake is designed to process big data at scale. It takes advantage of Spark, a powerful cluster computing framework, making it possible to scale workloads across many compute nodes. This results in improved processing speed and performance. Delta Lake also enables incremental updates and streamlined queries, allowing complex query operations to be performed more efficiently and faster. Delta Lake can also run on local servers as well as in the cloud.
Data quality and data management
Delta Lake provides mechanisms to ensure data quality and data management. By using Schema Evolution, data structures can be updated and managed without affecting existing data. This makes it easier to handle changing requirements and makes it easier for teams to work together.
Delta Lake also supports versioning, which makes it possible to access previous versions of data and track changes. This is particularly important for traceability and compliance requirements.
Reliability and recoverability
By using write-ahead logs and snapshots, Delta Lake ensures that data changes are secure and reliable. In the event of an outage or damage, data can be easily recovered without loss of data. This contributes to the security and stability of data processing and reduces potential risks.
Delta Lake use cases
Delta Lake can be used in a variety of use cases, including:
- Real-time analytics: Delta Lake can be used for real-time analysis of data streams to help companies respond quickly to changes and make informed business decisions.
- Machine learning: Delta Lake can be used to manage training data for machine learning models.
- Data warehousing: Delta Lake can be used as a data warehouse solution for storing and processing data.
- Data integration: Delta Lake can integrate and unify various data sources to help companies gain comprehensive insights from their data.
Conclusion: Delta Lake as a key technology for modern data architectures
Delta Lake has proven to be a game changer for big data processing. By supporting transactional integrity, scalability and performance, support for data quality and data management, and reliability and recoverability, Delta Lake provides a comprehensive solution for companies that want to process and analyze large amounts of data.
As a result, companies can gain valuable insights, make well-founded decisions and increase their competitiveness. Delta Lake has undoubtedly changed the way we process big data and will continue to play an important role in the future.
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