The role of the API in managing Big Data

Every time someone uses an app, information travels from a database to the user via an API. Single instances may not seem very important. As long as they perform the required task, people don’t think too much about how applications work. From a business perspective, though, the big data flowing through APIs could unlock important knowledge that helps tap into emerging trends and target customers better. To get the best results, though, companies need the best big data API management. In this article, we’ll discuss:

Big Data Basics

The Power of Big Data

Connecting Applications to Access More Data

Managing Your APIs and User Generated Data

Taking Control of Big Data for Deeper Insights

Big Data Basics

Before we dive into how APIs can be leveraged to get the most out of your organisation’s data, we’ll briefly describe how data is typically stored. Some of the most popular data depositories include Databases, Data warehouses and Data lakes – each with it’s own technology options, limitations and employment considerations.

Databases

• A highly structured option that can organize data according to your company’s apps and operations
• Retrieves information quickly
• Popular databases include MySQL, PostgreSQL, and MongoDB

Data Warehouses

• Organizes data by subject
• Can easily accept data from multiple sources
• Lets uses define their data retrieval parameters to identify specific information

Data Lakes

• Can store structured, semi-structured, and unstructured data
• Store raw data rather than processed data
• Extremely flexible but difficult for most people without tech backgrounds to use

DreamFactory keeps up with the latest data repositories by adding integrations as needed. Check our list of current integrations to help you choose a database, data warehouse, or data lake service that meets your needs.

The Power of Big Data

The amount of data generated around the world has grown at an impressive clip. Experts predict that the world will have 149 zettabytes of data by 2024. The size of just one zettabyte boggles the mind since its equal to a trillion terabyte hard drives. Just try to imagine 149 trillion hard drives packed with data. That’s what you can expect within a few years.

Companies understand the importance of big data. Big data and business analytics earned $189.1 billion around the world in 2019. Revenues will only increase as more people grow accustomed to using smartphone apps.

Why do companies spend so much money collecting, storing, and analyzing big data? Because they know that they get a strong return on their investment. When businesses learn to use big data, they often benefit from:

• Increased customer retention
• More successful marketing campaigns that target people in key markets and convert them into buyers
• Improved risk management that lets companies predict outcomes and develop successful business strategies
• Faster product creation that focuses on items that customers want to buy
• Shorter, less expensive supply chains that satisfy customers and lower costs

Big data does more than drive business success. Organizations also use big data analytics to:

• Evaluate investment portfolios
• Develop medications and other treatments
• Predict weather patterns and global climate change
• Personalize healthcare recommendations to improve health and lower costs
• Discover data abnormalities that might indicate problems like tax avoidance, drug trafficking, and violence

Big data has the potential to power the future of humanity. But it’s only useful when you know how to harness and analyze the information.

Connecting Applications to Access More Data

An individual API probably doesn’t see a lot of data, at least not enough for you to call it “big data.” Let’s say someone uses your mobile app to buy a train ticket. The exchange only requires a few bytes of data. You can use that information to improve customer engagement and discover features that will make your app more useful, but you probably won’t discover any significant consumer trends by analyzing it. Unless you have thousands of people using your app daily, you just don’t generate enough data to qualify as big data.

When you connect your app to multiple sources, though, you quickly increase the amount of data that you collect. Consider how much more data travels through your API when you use it to get ticket information from several databases. If you connect to 10 applications, you can expect your data to increase about tenfold. (Some sources will give you more data than others, so you can only think about this situation as a rough estimate.) Now, the data that you got from 10,000 users has effectively grown to 100,000.

Connecting applications to access more data can also produce deeper insights. When you have one result that says “Train A leaves City X at 10 a.m. and arrives in City Y at noon,” you only have six concrete pieces of information: the name of the train, the departure city, the departure time, the destination city, the destination time, and the time the journey will take.

You gain significant value by adding even one more result. By letting your mobile app connect to another company’s database, you can get a new result that says “Train C leave City X at 9 a.m. and arrive in City Y at noon.” At this point, you have the same six data points as the original result. You also have a new piece of information, though: the difference in travel time between the two options.

The value of your data grows exponentially as you use APIs to connect with more sources. It doesn’t take long before you start learning things like:

• Alternative routes
• Which train operators tend to have the shortest travel times
• Other cities where trains stop while traveling to the destination
• Your customers’ preferred departure cities, destinations, departure times, and arrival times
• The relationship between train operators, cities, travel times, and prices

The idea of adding more APIs to your app may sound challenging. It’s tempting to stay with the process you already use, especially if it works reasonably well. Luckily, you don’t have to spend a lot of time or energy managing multiple APIs.

The employment of a platform like DreamFactory enables businesses to effectively manage and orchestrate it’s suite of APIs. In this way, an API management platform can allow you to standardize and connect disparate APIs within a user-friendly interface. Other benefits of our API management platform include:

• Standardized security that protects you and users when connecting to third-party services
• API monitoring, logging, and audit trails that make troubleshooting easier
• Rate limiting and spike arrest features that will prevent your internal systems from shutting down when your app gets more traffic than usual
• REST API development that can support multiple architectures instead of just one custom service

Connecting with more data sources creates a larger net. Eventually, you can reach a point where your net gathers big data that you can mine for deeper insights into user needs. Of course, it works with much more than buying train tickets. You can use the strategy for anything from helping consumers compare shoes to giving people custom quotes for life insurance. Any data can become valuable when you learn how to use it.

Managing Your APIs and User-Generated Data

DreamFactory makes it easier for you to manage all of your APIs. You can still expect some growing pains as your business starts using APIs to collect big data. The good news however is that you can minimize these problems by taking a co-ordinated approach to managing your APIs and user-generated data. Central to effective API management is having comprehensive API documentation. Crucially, having your APIs effectively documented provides the building blocks on which ongoing API development and integration can proceed.

Last year, we published a blog post about tips to writing great API documentation. Now seems like a good time to revisit that topic because great documentation should make it easier for you to manage your APIs as you connect to more data sources and harvest more information. For an in-depth explanation of great API documentation, read the post from 2020. For now, follow these basic tips to make your job easier:

• Follow industry conventions so you can create consistent APIs that work with multiple apps and databases
• Use clear, concise language—avoid jargon!—when when writing documentation for decision-makers and developers
• Organize your API documentation in an orderly way that practically anyone can understand
• Provide a detailed description of the request/response cycle
• Use DreamFactory to automatically generate interactive Swagger documentation

Taking Control of Big Data for Deeper Insights

You will need the right tools to take control of big data and analyze it for insights. Not surprisingly, we think that DreamFactory does the best job because it has:

• Prebuilt API integrations
• Can automate processes quickly
• High security standards
• Scales horizontally and vertically
• Gives you live API documentation
• Runs on-premises or in the cloud
• Supports the most popular enterprise authentication solutions

If you want to explore other options, read our 2020 post Top 5 API Integration Platforms for 2021. Sign up for a free trial today so you can explore DreamFactory and decide whether it has the features that will make big data API management easier and more insightful. You don’t need to provide a credit card number, so you get a risk-free trial without any obligation.

Spencer Nguyen

As a seasoned content moderator with a keen eye for detail and a passion for upholding the highest standards of quality and integrity in all of their work, Spencer Nguyen brings a professional yet empathetic approach to every task.