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The amount of data that businesses collect, store and process has increased by several folds, and so have the complexities associated with data handling and data management. This situation calls for simpler and more reliable solutions for the big data needs of businesses and standardizing the data delivery file formats.
Unless you have a specific requirement where a certain file type is preferred over the other, you might easily get confused by the different options available. We’d be demystifying the different data delivery formats’ pros and cons in this post.
Data Delivery File Formats
1. CSV
CSV is a flat structure data format that is ideal only for small applications. Compared to XML and JSON, CSV demands less technical skills and can be accessed using most applications. The downside of using CSV is that the encoding has to be set in the application which handles the file for all the characters to display properly. CSV is not recommended for large-scale and complex data projects.
2. JSON
JSON is a very flexible data format that supports the nested structure, meaning your data points can have multiple subcategories. Handling JSON format requires slightly less processing power compared to its counterparts and is also lightweight. The only con is that a parser has to be programmed to access the data in a JSON file which might demand technical labor. JSON is the recommended data format for complex and large-scale applications.
3. XML
XML is similar to JSON in many ways apart from a slightly higher processing power requirement. It supports nested structures like JSON and is the most popular data format on the web. If you are using the data for web-related projects, XML can be a great fit.
4. MS Excel
MS Excel is not a suitable data format for any serious big data project and is not offered as part of our solutions. You can read more on why MS Excel is not a good fit for data projects.
Modes of Data Delivery
1. Dropbox
Dropbox, being a consumer-focused service is extremely easy to use. However, it has limits on the storage capacity and may not be a good option if you are expecting large amounts of data.
And in an era of expanding data landscapes, adaptability is crucial. You might need data in different formats to meet certain objectives. That only adds more insult to the injury in terms of storage space, but users have a way around this problem, nonetheless.
Thanks to modern-day IT tools, one popular solution for many is to convert PDF files online into formats that best suit their needs or compress some to minimize storage costs while streamlining data handling processes.
2. Box
Box works similar to Dropbox and can be a suitable solution if the expected data volume isn’t very high. It is also user-friendly and can be especially great if you’re not familiar with the likes of AWS and Microsoft Azure.
3. PromptCloud API
We deliver the data through our own API as a free option for accessing the data. Fetching the data from API would require some technical skills but is an ideal option if you can build an application for extracting data as soon as it becomes available. However, if your data includes files like images or PDFs, the API cannot be used and you would have to opt for a file upload option.
4. Amazon S3
Amazon S3 is a great and versatile option for enterprises with complex and large-scale data requirements. Owing to its robustness and security features, S3 makes for an ideal data delivery mode. If you are ever in doubt about which delivery mode to go for, S3 is a safe bet.
5. FTP
We can also push the data directly to your own FTP server. This delivery mode works just like any other option but the security aspect of your data should be handled internally and that could be a challenge for many small businesses.
Note: Apart from the above-mentioned delivery modes, we’re also open to upload data to Microsoft Azure and Google Cloud.
Factors to Consider while Choosing your Data Delivery Format
1. Compatibility with your System
You should check for compatibility between your existing big data analytics system and the delivery format and mode. Although this is a no-brainer, compatibility issues at a later point in time could end up in you having to re-process massive amounts of data which is not very convenient and not to mention a waste of time, effort and cost.
2. Flexibility
It is a good idea to always opt for flexible data formats since it leaves more room for tweaking if you decide to rebuild your big data system. Simply put, flexible formats give you more possibilities compared to rigid ones like MS Excel which is only good for limited and small-scale projects.
3. Processing Power Requirements
The processing power requirements vary depending on the data format and delivery mode you opt for. Some formats are a bit more resource-hungry than the others and you can go for the one that fits your bill.
4. Storage Space
You should have a clear idea about the data volumes that you’re expecting from the web crawling project and opt for a data delivery mode that can handle such volumes. This would help you choose the optimal delivery options and help avoid bottlenecks at a later point in time.
Conclusion
Choosing the right data delivery format and mode will have a long-term effect on the ease of data handling operations in your organization. Compatibility, flexibility, computing power requirements and storage space are some of the crucial things you should factor in before choosing a data delivery method. Your delivery formats will also define if or how you can scale your big data pipeline. Evaluating various data delivery formats with their pros and cons will help you make the right call when it comes to choosing the right one.
