Manage data pipelines completely in the cloud
Building a modern data stack is not magic. Especially not when complex and multi-level data transformations are available both via code and no-code on a single platform for teams with and without programming knowledge. This is proven by the Berlin-based company Y42 proves this with its tool of the same name, which simplifies the creation and management of data pipelines for companies in an almost magical way.
Most companies are aware that they need to do much more with their data. At the same time, they lack an overview of the options available to make this possible. They have an idea of the big picture, but are unable to identify the individual elements required and put them together appropriately - and deciding between the various tools is indeed extremely difficult without understanding them in detail.
In various companies, we have then heard thoughts such as: Are such powerful tools the right thing for my company, or is this step too early? Should I expect to have to capitulate to a project that is too complex? Where can I find employees who can implement such tools?
Building a data stack with Y42
Y42 interrupts such nervous thought processes in an ingenious way. With them, companies no longer have to put together their data stack (the tool landscape with which data can be processed) completely by themselves, but instead use familiar and established tools on the Y42 user interface.
They use the best-in-class tools that they would otherwise have to set up on their own. These include the cloud data warehouses Snowflake and Google BigQuery, the Airbyte tool for data integration and dbt Core for data transformation and modeling. These tools are based on open source standards, meaning that Y42 is open and highly compatible with other or existing stacks.
The DataOps Cloud also follows a combined code & no-code approach and can therefore be used by people with and without programming knowledge. It promises production-ready data pipelines and comprehensive management of data operations (DataOps), for example with regard to data governance and collaboration with colleagues in the data team as well as in business teams. Y42 is based on the most common cloud data warehouses Snowflake and Google BigQuery and is therefore compatible with most requirements.
The use of Y42 is therefore so irresistible because nobody has to deal with the selection of tools within the data stack at a deep level of detail. Anyone who is already thinking in terms of a modern data stack and wants to build one will benefit from Y42's intelligent tool selection, save time and money and improve the quality and usability of their data. Dedicated knowledge in the field of data engineering is not necessary for all of this, but can be an excellent supplement if required.
Legacy data stack vs. modern data stack
Why do the cloud and the modern data stack play such an important role here? First of all, a data stack is a combination of technologies and tools that work together to store, process and analyze data. The aim of the data stack is to enable companies to transform raw data into valuable data for analysis and AI. Essentially, to use a data stack, we need a database for data storage, a backend system for modeling and processing the data, and a frontend application that allows us to view and interact with the data.
A distinction is made between the Legacy Data Stack and the Modern Data Stack. While legacy data stacks require at least one server, modern data stacks are cloud-based. This makes them more scalable and flexible.
The Modern Data Stack can be deployed immediately and agilely as data sets and workloads grow. It then simplifies access to shared data. Last but not least, it enables companies to make their entire data pipeline available quickly - without being restricted by a hardware setup. The data infrastructures can therefore grow with their data requirements without incurring costs or scaling failures. They also have fewer barriers to the integration of additional tools.
Transformation of data and data pipelines
Even in the Modern Data Stack, valid data analysis can only be performed with functioning data pipelines. The question is therefore not whether data pipelines should be set up, but how and with which resources this can be done. This is where the Y42 data platform plays a key role.
After all, data analysis is a highly dynamic process: data is extracted, transformed, combined, validated and loaded. Data pipelines ensure automated processes on the one hand and keep the movement of data stringent and consistent on the other. With data pipelines, companies ensure the professional preparation and processing of their data. Data ingestion, i.e. the connection of data, is an important basic building block within the Modern Data Stack and requires a reliable structure. Y42 fulfills this structure perfectly.
Y42 is the new way to manage a modern data stack
Y42 is based on some of the best-of-breed tools on the market. It uses the computing capacities (compiled against the database) of Snowflake or BigQuery. Finally, the data is imported into Tableau or similar BI platforms. Y42 is therefore an orchestration tool for all tools in the Modern Data Stack and enables them to work together seamlessly. Companies that already use the data stack that Y42 also manages can migrate their stack very easily and quickly.
Due to the use of the various tools and SQL required for the transformation, the data modeling process could previously only be implemented with data experts and knowledge of data engineering. This traditional fact is completely invalidated by Y42 and the process of data modelling is revolutionized.
Y42: "Mission Control for your data pipeline."
Y42 makes life a lot easier for companies and their data teams through tool accessibility, seamless collaboration and comprehensive data governance.
Because the tools are managed by Y42 and are immediately accessible to everyone, users can start modeling data and ultimately generating insights straight away. Users no longer work with data alone, but can collaborate with their or the business team to extract and understand the real value from the data. Y42 simplifies this with version control, in-app chat and an easy-to-understand data catalog.
At the same time, despite more users in the data stack, no chaos should arise, as this is the major risk when trying to operate the modern data stack just like that. This is why Y42 attaches great importance to data governance. All data-related activities can be observed and monitored. In addition, asset ownership, a data catalog, data contracts and multi-level access control help to implement a data governance strategy.
Companies that already have their own database (Snowflake or BigQuery) and want to build their Modern Data Stack on top of it can simply use Y42 and experience the flexibility, scalability and independence of the tool for themselves - and perhaps a little magic too.
