Product Overview

Embedded analytics is a highly contested field where analytics are embedded into different applications, versus delivering analytics via a specific, standalone application. With embedded analytics, you can build your analytics platform into specific applications like your CRM or marketing automation platform.

And in this realm, there are a few major players who dominate the ranks of software. Among those titans are Sisense and Logi Analytics.

Sisense is a powerful solution that offers robust and fully-featured business analytics, such as interactive dashboards and real-time and predictive analytics.

Logi Analytics is an embedded analytics solution that offers multiple, state-of-the-art features, such as secure authentication and flexible themes.

Background Processing

Recognized as a high priority by SelectHub’s analysts, background processing is what goes on behind the scenes when you’re not looking. Background processing is the act of ingesting large amounts of data and processing, preparing it, and just generally working on it during off-hours in the background.

Background processing is something that can be built into an application, or handled via third-party developers who use the embedded application in the background. In this realm, the point goes to Logi Analytics. In the battle of Sisense vs Logi Analytics, this one has to go to Logi for their powerful API.

Logi analytics offers customers (specifically developers) different configuration options such as request parameters, request tokens and more. This gives developers the ability to access the application from outside its dedicated window or panel, and have it process data in the background, as opposed in the foreground.

Your IT department will be happy to be able to build so closely to Logi’s API; not to mention, Logi is an adaptive program already. Even its themes are built to take on the look and feel of the software it’s being embedded into.

Integrated Workflows

Workflows are essential to everyday business operations, yet can be somewhat hard to describe, or even visualize. Essentially a workflow is what you accomplish in the day and how you go about accomplishing it. A workflow is all about flowing from one thing to the next.

In a more modern sense, this might look like coming into work, checking your email, responding to some urgent messages, opening up a spreadsheet and entering some numbers, and then using those numbers elsewhere in a professional document.

See how tasks flow from one to another? Now, software can help augment this process, and most analytics platforms include some sort of integrated workflow. In the realm of Sisense vs Logi Analytics, we’re going to have to give another point to Logi.

Logi offers powerful workflow integration features, whereas Sisense just doesn’t. Logi predicts workflows for the end user, giving them sophisticated automation processes — such as triggering a report or email — all without ever having the user leave the host application at all.

They’re what you accomplish in your day-to-day working hours. And when you’re working exclusively in a single application for long periods of time, workflows become important. You want to have a good picture of your day-to-day operations and optimize your workday. Logi helps you do that, whereas Sisense does not.

Built-in Alerts

Alerts tell us urgent information as it becomes available. They’re essential to our day-to-day operations. When it comes to software alerts, the idea is pretty much the same, only these alerts can usually be configured in all the best kinds of ways; either customized to go off at a certain time; customized with the right information; turned off altogether and more. These all fire off within your application window, or maybe to your email; but the point is that software is triggering these alerts.

Where Logi Analytics falters, Sisense prevails. But the Sisense vs Logi Analytics cage match is not over yet, folks.

See, Sisense’s built-in alert system actually beats out Logi’s. With Sisense, users have the ability to powerfully integrate alerts and notifications into their workflows and set custom alerts and reminders for their data.

Even more powerful is the way alerts are triggered for Sisense. With Sisense’s software, users can set up custom alerts to be triggered when certain criteria are met. For example, when one of your KPIs is achieved, you can have the software notify you via in-application alerts or emails. And since it’s an embedded analytics product, you’re getting the alerts in an already work-saturated product, keeping you inside your workflow.

Row/Column Level Security and User Filtering

In the current year, data security and privacy are essential. But this doesn’t always mean protecting sensitive data from hackers (though you should). It can also mean making sure your employees don’t see or manipulate data that they’re not supposed to or only see data that they should be allowed to see.

We call this row/column level security and user filtering, and though both applications have this feature present, Sisense just does it a little bit better.

Sisense gives the admin the ability to assign roles and permissions to each member or team involved in an organization, outright preventing the wrong data from getting in front of the wrong people. And what’s powerful about this is that it can also give users access to just the right data that they need.

We’ve all been there: A complex (albeit powerful) spreadsheet that you can’t understand or don’t want to traverse to find what you’re looking for. That’s where Sisense’s user filtering comes in. Admins can pick users (or user groups) to assign to certain data drill-downs or filters, showing them only what they need to (or want to) see.

Your users get a stripped down version of the data they need, and none of what they don’t. And that’s not only good for productivity but security as well. If an account is compromised by a hacker, they won’t be able to see anything past your filter or security settings, meaning you’ve just secured yet another attack vector.

And we didn’t forget to mention the fact that Sisense offers you the ability to encrypt data and reports from the ground up. Utilize the following encryption algorithms to secure your data:

1. SHA-256
2. TripleDES
3. AES-256

Even for data at rest, Sisense is compliant with on-disk encryption programs like Windows file encryption and EFS. And that’s why Sisense wins this round. Both products take security and privacy seriously, but Sisense takes it just a step further.

Compare Sisense and Logi Analytics Against Your Needs

Descriptive Analytics

Ahh, descriptive analytics. The bread and butter of analytics. Without descriptive analytics, we have no real idea of what’s going on with our business operations.

In essence, descriptive analytics is your window into the past and your look into the present. It describes analytics as they are in the now by looking at historical and current data, and offering insights into that data. It can be used across industries and sectors, such as in healthcare or inventory tracking.

But in this round of Sisense vs Logi Analytics, it’s actually a tie, believe it or not. To not have a powerful descriptive analytics package in your embedded analytics software is like trying to have apple pie without any apples, so picking between the two wasn’t just a hard task — it was nearly impossible.

Both products do a great job of ingesting data, analyzing it, and presenting it in digestible reports. And yes, they all have predictive analytics capabilities as well, in which they take the previously harvested data, analyze it, and then make predictions based on said data.

Siesense’s descriptive analytics package is one of the best in the industry; winning awards such as the BIG Innovation Award for business intelligence. Logi Analytics has its own share of victories as well, such as being recognized by Gartner as a leader in embedded analytics.

Flat Files Integrations

Flat files make the world go round. They even make this article possible, in fact. Don’t know what a flat file is? It’s a file with no inherent hierarchy or relational structure. So typically this is a text file of some kind without any markup.

So what do flat files have to do with embedded analytics?

Well, lots of potential data comes in flat files. For example, the popular “comma separated values” format, otherwise known as CSV, is often used to store large quantities of data. The CSV can be exported from popular programs like Microsoft Excel or Google Sheets.

Importing data previously stored in more primitive applications (or is, for the foreseeable future, going to be entered and stored in a flat file) is a basic function that we like to call “integration.” You could probably see integration’s relevance when dealing with both an embedded analytics product when your workflow requires you to enter data into something like a spreadsheet.

We have to give this one to Sisense. Sisense offers a superior product when it comes to flat file integration, in that it REALLY integrates the flat files with its embedded analytics solution. It works with things like simple CSV files, and also integrates with cloud solutions like Google Sheets.

Being able to pull data from flat files is an invaluable addition to any embedded analytics solution because it doesn’t break your workflow and it allows for diversity of data sources.

Big Data Integration

We’re going to wrap up our Sisense vs Logi Analytics conversation by talking about the big brother of regular analytics: big data.

But what is the difference between big data and, well, regular data? We’ve got more in-depth answers in this article, but for a more condensed answer, we’ll briefly explain it here.

Big data is, and we quote, “large data sets that outgrow simple databases and data handling architectures. For example, data that cannot be easily handled in Excel spreadsheets may be referred to as big data.”

Essentially, it’s large quantities of data that cannot be stored in traditional or simple databases. And unsurprisingly, a lot of industries have a lot of data. According to Raconteur, by 2025, humanity will create 463 exabytes of data every day.

Think about industries like healthcare; They create petabytes worth of patient data each day; from medical records to uncompressed and lossless image files. That’s a lot of data that needs to be processed, and an embedded application is just the application to do it.

In this final round, we’re going to say it’s a tie. Sisense offers fantastic integration with hardware and software stacks from Hadoop Hive, Hbase and more. That’s not to say that Logi Analytics doesn’t also do a stellar job of integrating with big data sources; They do. They’ve got partnerships with leading big data providers like Amazon and Google, and continue to expand their repertoire daily. It’s hard to go wrong with either choice.

Compare Sisense and Logi Analytics Against Your Needs

Who Won?

After a brutal cage match between two of the leading embedded analytics platforms and tallying up the scores we’ve handed out, the winner of the Sisense vs Logi Analytics fight of the century is … Sisense.

Sisense delivers a superior product compared to its counterparts, though Logi is not far behind. With stellar big data integration, data security, flat files integration and more, Sisense just barely edges out Logi Analytics to take the crown in most instances.

Despite that, there’s still a case to be made for Logi Analytics as well — it’s all about what level of capability you’re looking for. Logi Analytics performs really well in a lot of areas where Sisense just can’t keep up. Background processing and integrated workflows are integral features for an analytics product, and Logi just works better when it comes to constantly working in the background and integrating workflows.

Think hard about what you really need from your embedded platform (and maybe consider checking out our requirements template) — is it every feature under the sun? Because Logi might not do things as well as Sisense overall, but they can be a flexible option too for the right company.

Do you use any of these data embedded BI platforms? Which do you prefer? Let us know in the comments below!

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