Synapse Review- Everything You Wanted to Know About It

Research in any field has become increasingly become data driven. Data, in this sense, isn’t exclusively relegated to quantitative data. The upward trajectory of Data science has allowed data scientists to analyse all forms of data. Typically, researchers deal with large sets of data and collaborate with their team-mates to draw meaningful conclusions. Therefore, it is imperative that they have the right tools with which they can easily manage their workflow. Every research undertaken by someone establishes the foundation for future research. Thus, having a tool with which researchers can boost their productivity is imperative for effective research.

Synapse is a tool that helps researchers with this. This article evaluates the effectiveness of Synapse as a research based collaborative tool. It further evaluates the pros and cons of using it to draw up whether it is worth the attention.

Synapse Explained

Synapse is an open-source, intelligence analysis platform which assists researchers in drawing meaningful conclusions from data sets generated from different disciplines. Complex research questions require data to be collected from different disciplines and Synapse assists analysts and algorithms answer those questions.

In a nutshell, Synapse presents data, code and text in an integrated manner. It also provides “provenance” support. Provenance is a result which is obtained by using a combination of data and code. The data and code used in this context are either used or directly executed.

How Does Synapse Work + Installation

Synapse works with a host of programming clients. R, Python, Command Line and Java are some of the platforms that support Synapse. As an example, say you are looking to install Synapse as a Python package. To do that, download the Python Package and follow the instructions to install Synapse onto Python. However, to start using it, users need to create a Synapse account. Once they register for an account, only then can they start creating Synapse objects.

Advantages of Using Synapse

Besides being an effective data management tool, Synapse offers a range of benefits that extend beyond that. Here is an overview of some of the important features: -

1. Flexible Data Model

While it incorporates data from different disciplines, it also accommodates obscure data types. Its hypergraph framework makes representation of widely disparate data types possible.

2. Shared Analysis Framework

Its focus on providing a streamlined workspace makes way for effective collaboration within teams. Analytical knowledge resides in a central framework rather than being located in a specialized research group. It also shows live changes to file types which is similar to that seen in Google Drive.

3. Better Automation

By building an automated model, researchers can automate routine tasks and save time. Synapse leverages the Storm query language, implying that tasks can exclusively be automated as a Storm query.

4. Thorough Logging

Synapse generates a log of reversible changes known as “splices”, which hold every change ever made in a hypergraph. It is made possible by holding the provenance of the change, which keeps track of every change made in the hypergraph. Do note that changes can either be manually made by an analyst or by using an automated process.

5. Support for More Modules

Synapse supports third party modules, which is essential for majority of researchers. Since research compounds over time, there is a good chance that researchers could have used different methods to analyse their data. If they were to adopt using Synapse, they could bring their existing research into the system and it will easily integrate into Synapse’s ecosystem.

So, is Synapse worth It?

Synapse is definitely worth it, especially if you’re an academic researcher. As noted earlier, Research requires keen attention to detail skills on the part of researchers. The last issue that they need to worry about is that of their tools. While Synapse does require technical expertise and has a learning curve associated to it, it can bode fruitful returns if used correctly.

If you’re a team of researchers looking for an effective collaborative tool, Synapse is worth checking out. Synapse 2.0, which is the latest version of it, brings better backwards compatibility with it. Backwards compatibility is imperative for a collaborative tool’s success because it allows new researchers to effectively come onboard. Improved admin support, View/Layer Management and Trigger Management are other reasons why it is a great collaborative tool.

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Rhett Greenhagen

Rhett Greenhagen

“I am always ready to learn although I do not always like being taught.” — Winston Churchill

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