Data Platform
Using a data platform, you can get a more robust view of your data and manage it easily and effectively. There are many different types of data platform services. Therefore, you should aim to find a platform that specifically meets your needs. If you’re a data engineer, for example, you should seek out a platform for data engineers. Similarly, if you’re looking for a cloud-based solution as opposed to an offline platform, you might narrow your search to online platforms only. This can make it easier for you to find the most appropriate cloud data platform for your unique business needs.
One of the critical aspects of working with a data platform is that you can compile your data in a single location. Rather than having to pull data from disparate systems, you can easily access what you need from one platform. You can more easily keep track of your data. Quickly spot issues as they occur. Work to resolve those issues promptly. Data platforms provide tools to monitor data pipelines, ensuring efficient utilization.
Acceldata is a data observability platform that offers complete visibility into data performance, allowing users to make the necessary changes to improve data quality management. Acceldata predicts operational issues before they spiral out of control, correlates events, and helps organizations avoid poor business decisions due to unreliable data. The platform offers three products (Pulse, Torch, and Flow), each of which play a critical role in helping users sort and analyze data for maximum efficiency. With Acceldata you can get more out of your data system and drive greater revenue, ultimately promoting business growth across the board.
Data Platform Architecture
Data platform architecture outlines steps for capturing and delivering data quality. In contrast, data observability architecture offers holistic visibility into the data management process. This enables users to better understand data origins, destinations, and its potential for enhancing business operations. Big data platform architecture is likewise useful for understanding big data, or data sets that are so large that they cannot be appropriately stored and processed by standard data tools. Different architectures are most useful for different types of data, and so it’s important to consider the type of data you’re working with and what you’re hoping to do with it.
You can view a data observability platform architecture diagram to learn more about data observability architecture. This can give you a better sense of how different aspects of observability impact one another and what’s all involved in monitoring data quality. By understanding each of the data platform layers, you can better optimize your monitoring process. You might also study a modern data platform architecture to learn more about how to modernize your data system for better results.
Data Platform Tools
Data platform tools enable users to monitor their data. But what is a data platform? As discussed previously, data platforms extract, analyze, and store data, making it easy for businesses to manage their data in a centralized location. Just as there are different data platform types, there are different types of data platform tools. For instance, if you work for an enterprise company with large volumes of data, you might look specifically for an enterprise data platform. This may be better suited to your needs than, say, a platform designed for small businesses responsible for smaller volumes of data.
There are a wide variety of data platform companies, so when looking for a data observability platform, it can be helpful to outline your specific needs in order to narrow down your search. If you use Apache Hadoop, for example, then data platforms Hadoop tools may be most useful for your specific needs. It’s important to choose tools that are as closely aligned to your software or framework as possible. This will not only allow you to get full visibility into your data workflows but ensure continuity and prevent errors. Defining your specific needs and requirements ahead of time can help you choose the right tools for your data.
Data Platform Examples
Viewing examples of data platforms provides insights into managing your own data platform. It also clarifies the distinction between data platform and database, often used interchangeably but referring to different concepts. With various types of data platform examples available, you can find one that suits your specific needs. For instance, exploring customer data platform examples is beneficial for those handling customer data, while researching top data platforms helps identify the best overall solutions.
Different data platform companies offer different capabilities and integrations. For example, Acceldata offers support for Hadoop users, allowing them to cut costs by 50% or more. Users can remain on premises with the Hadoop release they have now without the need for continued Cloudera support. Boasting the best Hadoop SLAs in the industry, Acceldata enables users to optimize their ecosystems and get more out of their software, even as Cloudera sunsets support for HDP/CDH. Those that are looking for data platforms Hadoop solutions can find value in Acceldata’s multidimensional data observability platform.
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Data Platform Gartner
Data platform Gartner tools are extremely useful for comparing platforms. Browsing the Gartner Market Guide for Customer Data Platforms provides insight into existing platform types. It offers clarity on the diversity of platforms available today. Viewing examples of customer data platforms demonstrates how they operate and their organizational benefits. Each company offering these platforms provides unique tools and solutions. Thoroughly assessing options ensures finding the best platform for your business needs.
The Adobe customer data platform is highly utilized in the market as a CDP. It provides users with real-time visibility into their data, enabling collection and unification for activation purposes. Other top customer data platforms provide similar functionality and are critical for understanding data on a deeper level. Acceldata is unique in offering multidimensional observability. This allows users to gain a comprehensive view of their data from all angles. It helps drive better decision-making processes. The platform gives users the tools they need to optimize their data systems and ensure quality across all layers. This can result in higher data engineering productivity, quicker application development, and fewer incidents.
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