In turn, it is well known that there is a need for data to communicate with each other. From this point of view, why not consider a platform that unifies environments in a single place as a data management solution?
Databricks, a platform known in the market as a Data Lakehouse, offers exactly this performance. As an environment for data use that contains workspace, repositories, data storage and clusters – a set of machines –, workflows and cloud space in a single place, it is possible to scale gains and make it an agile and collaborative analysis, facilitating processes.
How does Databricks work?
The dashboard works in such a way that raw data is stored on a large scale and in different formats.
It is possible to include structured, semi-structured and unstructured data.
1. Structured data
They are basically data in columnar forms, as in transactional environments, databases or ERP systems.
2. Semi-structured data
They are data in flexible schemas with more or less fields, but which also follow a standard structure, such as the JSON (JavaScript Object Notation) file.
3. Unstructured data
These are audio and video files, as well as XML.
Furthermore, Databricks offers other possibilities such as:
Transaction support, allowing writing to the same file simultaneously;
Predefined schemas, improving data quality;
More refined data governance, making it easier to manage meta data;
High scalability power, thinking about cloud architecture, since it is possible to vietnam phone number example provision an even more robust cluster for a process;
Support for real-time processing, where within Databricks it is possible to work on embed loads and weekly loads, in addition to streaming in real-time processing (transmission of continuous data flow).
From this point of view, it is understood that Databricks combines the best and greatest flexibility compared to other platforms on the market.
Not to mention that it is present in the three main clouds on the market, such as Azure, AWS and Google.
But how does Databricks actually become beneficial for a business? We explain.
What are the benefits of Databricks for your business?
Initially, because it is considered a data lakehouse platform and combines the best of these worlds, Databricks is nothing more than a facilitator when the topic is delta data laker.
This is because there are refined layers of data governance, being a collaborative platform in which data engineers, scientists, machine learning professionals and many others can work together within the same place, facilitating the entire implementation of an architecture.
In this way, thinking about business, Databricks reinforces other points, such as:
It has unified processing with significant data volumes or from many users;
Scalable data storage, simple and agile;
Workflow programming dynamics;
Presence in AI (Artificial Intelligence);
Data processing;
IoT (Internet of Things) Analysis;
Use of Databricks peripheral solutions to control extra costs;
It has a cost advantage, contributing to business savings and being attractive to areas of engineering, algorithms and AI;
Report generation without being dependent on a cloud, such as AWS, Azure and Google, making the use of multiclouds easier.
Another great benefit is that there is no exception for the use of Databricks. In other words, any business segment can use the platform for data usage.
How to understand the platform for a data business?
On the technical side, Databricks provides a notebook view. That is, a kind of view that resembles a book and includes several technology languages, such as SQL and Python, through cells, which can be handled within this single 'sheet'.
With this in mind, working with data can be much more dynamic and interactive for a team that models this information and needs to talk to each other.
This format also allows you to upload files from other locations, use data sources and make connections with Azure and other databases, whether relational or SQL, with several other apps and around 150 data sourcers.
That is, you won't have to completely lose your data or have to redo services.
The use of clusters and the scalability of using these machines are easy to provision, not to mention that they are only paid for when active, and if inactive, there is no charge, acting completely automatically, as long as the provisioning of the clusters is carried out consciously.
In addition, MATH TECH has certified professionals, and if you have questions or are looking for facilitators for using Databricks, this is the right place.
How do you know if Databricks is right for your business?
Arriving at this solution is nothing more than evaluating whether a robust data environment is necessary for processing a significant volume of data, if one is available.
The right thing to do, then, is to assess whether the customer profile generally consists of many users, with problematic data governance and misuse.
And at MATH, we propose means of scalability that require this more refined governance, due to the size of the environment.