Understanding Data Latency: 3 Critical Aspects

Data Latency is a key metric that helps determine the effectiveness of Business Intelligence Software. As technology advances, businesses strive to build more sophisticated products. This makes the faster delivery of data that much more important. This makes it crucial to understand the basics of Data Latency along with its importance.

In this blog post, Data Latency will be discussed in detail. It will also cover the differences between Data Latency and Bandwidth, the effect of Data Latency on Throughput, and the Data Latency measurement process.  

Table of Contents

• What is Data Latency?
• What are the Applications of Data Latency?
• Data Latency vs Bandwidth
• What is the Data Latency Measurement Process?
• What is the Effect of Data Latency on Throughput?
• Conclusion

What is Data Latency?

Latency is the term used to measure delay. Data Latency refers to the time the data takes to arrive at a destination from a source across the network. Often, it is measured as round trip time, i.e. the time data took to get to the destination and arrive back. 

As data is being transferred from the source to the destination, which is probably on a different network, it is essential to measure round trip delay as the destination might be using a TCP/IP connection which may send limited data. Hence, there might be a delay in receiving the data back. Thus, the round trip delay has a crucial impact on the performance of the network.

Latency is usually measured in milliseconds (ms) and is generally called Ping ms.

Four main components that affect Data Latency over the network are as follow – 

• Transmission medium: Data transmission majorly uses the physical medium for communication from the start point to the endpoint. The old physical medium uses copper-based cable networks, which affects the network and causes higher latency. Nowadays, modern optical fiber tends to show very little latency of the data. Wireless transmission also has faster data transmission. 
• Propagation: Propagation means how far the data is being transmitted. For example, the data/packet going on a round trip across the world is 100ms. However, it may be lower in the case of a direct connection between two nodes.
• Routers: The efficiency of the router has a significant impact on latency. A good router can decrease the latency to a great extent.
• Storage delays: Data Storage system significantly impacts the data transfer as the time taken to read data added to the transmission time. For example – the HDD vs SSD can have a significant impact on data transmission. 

What are the Applications of Data Latency?

In an ideal situation, low latency seems desirable. However, for use cases that don’t need real-time data higher latency is acceptable. For instance, generating quarterly sales reports. But for more sophisticated use cases that run on real-time or near real-time data, low latency is a high priority. Here are a few examples of use cases that benefit from low Latency:

• Optimizing the front page of a news site that displays breaking news stories.
• Balancing supply and demand in a two-sided marketplace with the most accurate and up-to-date information.
• Making content or product recommendations by taking the recent actions of users into account.
• Detecting suspicious or fraudulent behavior in real time.
• Retargeting customers in real-time who may have abandoned their cart or interacted with an ad.

For each of these use cases, low latency is highly desired since real commercial value can come from the data being acted on more quickly.

To put this in perspective, the faster a marketplace can ensure sufficient demand for the supply available, the better will be the experience for buyers and suppliers in the marketplace. Similarly the faster a bank can spot potentially fraudulent transactions, the more it can focus on minimizing the cost of containing cases of fraud. When a news site displays content on its front page that is particularly relevant to the current news cycle, it can increase the likelihood of readers popping back regularly throughout the day.

Data Latency vs Bandwidth

People often get confused with latency and bandwidth, as both go together. Bandwidth refers to the network capacity to transmit the data across the destination, whereas Latency is the measure of time that data took to reach its destination. It is a measure for round trip time, i.e. from source to destination and then back to the source.

Bandwidth is measured in bits per second or commonly Mbps (Megabits per second). The higher the bandwidth, the more data or simultaneous data it can carry and transmit at any given point in time. The Bandwidth of a network or a network circuit refers to its capacity to carry traffic. It is measured in bits per second, commonly Megabits per second (Mbps).

To use an analogy: If Bandwidth can be considered a road, the wider the street, the more the traffic. Latency, on the other hand, measures how much time one takes to reach the other end.

What is the Data Latency Measurement Process?

High latency can have a severe effect on the performance of your application as it reduces the response time of your application to the users. To measure or check the latency between your system to the destination, you can type the destination’s web address or IP address. A typical example can be – 

You can check the network latency of your internet connection with any website bypassing its web address or IP address in the command prompt on a Windows or Mac. Here is an example of the command prompt on Windows:

C:Usersusername>ping www.google.com
Pinging www.google.com [172.217.19.4] with 32 bytes of data:
Reply from 172.217.19.4: bytes=32 time=47ms TTL=52
Reply from 172.217.19.4: bytes=32 time=45ms TTL=52
Reply from 172.217.19.4: bytes=32 time=47ms TTL=52
Reply from 172.217.19.4: bytes=32 time=43ms TTL=52
Ping statistics for 172.217.19.4:
    Packets: Sent = 4, Received = 4, Lost = 0 (0% loss),
Approximate round trip times in milli-seconds:
    Minimum = 43ms, Maximum = 47ms, Average = 45ms

Here you can see the result of pinging www.google.com. The statistics show that the average time it takes for a roundtrip between the given PC and Google’s network is 45ms.

What is the Effect of Data Latency on Throughput?

Throughput is the measure of the number of bytes written per second. Or it can be defined as the amount of data transmitted to a destination in a given time. With Data Latency, throughput is adversely affected. 

Imagine a scenario where the network path is like a curvy pipe, water is the data that’s been transmitted through the pipe, and the bucket is the destination. When discussing data transmission, you have to look at TCP (Transmission Control Protocol), ensuring that all the data reaches the destination safely and in the correct order. This requires an acknowledgment from the destination before sending new packets of the data. 

In a real-life scenario, the bucket size is usually 64 KB (TCP Window). Thus, the TCP protocol prevents you from sending more than 64 KB of data at a given time without acknowledgment. The greater the time of acknowledgment, the greater is Data Latency and hence lower throughput.

Conclusion

This blog post discussed Data Latency and how it is measured, how it is different from bandwidth and throughput; and the effect Data Latency has on throughput. 

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