IT Operations Analytics vs. Data Visualization Tools

IT Operations Analytics vs. Data Visualization Tools

www.loomsystems.com

http://www.loomsystems.com/

INTRODUCTION

Data visualization describes any effort to help users understand their data by

placing it in a visual context. Patterns, trends and correlations that go undetected in

text form can be exposed and recognized easier with data visualization software.

Operations Analytics is the science of examining raw operational data for the

purpose of drawing actionable conclusions from that information. It is used in many

industries and disciplines to direct decisions and scientific understanding.

Data analytics and data visualization certainly do fit together. In fact, data

visualization is often a component of data analytics. But while most Operations

Analytics software vendors embed data visualization tools into their products, they

don’t necessarily have their own algorithms producing new insights from that data.

In itself this isn’t a bad thing – it’s just not true data analytics. The job of these

companies is to package and deliver data in appealing ways, which is only part of the

analytics puzzle.

A complete ITOA solution is comprised of several

components to first prepare data and then to analyze

it. Certain vendors offer only a partial solution but

still label it as “Operations Analytics”.

Such differences may be hard to spot at first, but can

have a potentially huge impact on the long term

success or failure of the selected solution within your

organization.

Loom Systems | www.loomsystems.com I [email protected]


THE CASE FOR OPERATIONS ANALYTICS TOOL

While visualizations can be useful for Operational Analytics purposes, data

visualization tools cannot be considered a complete analytics solution since they do

not provide advanced analytics or scalable data storage and management features.

Yet, some of data visualization tools cost as much as full-fledged analytics solutions.

Data visualization is a useful component of data analytics, not a complete solution.

This distinction can be made clearer by use of the following example: imagine being

asked to pick out one shade from a palette of 40 different shades of white. The

number of options will likely overwhelm you, and you couldn’t make a decision or

come to a conclusion about the value of one shade over another.

A similar thing is happening with data visualization. We’re seeing the same data sets

expressed through 40+ visualization methods. Quite simply, it’s too much.

For this purpose we often employ a data scientist. The focus on the data scientist

often implies a centralized approach to analytics and decision making; we implicitly

assume that a small team of highly skilled individuals can meet the needs of the

organisation as a whole.

The problem is, we have so much of one type of data, and so many ways to slice and

dice it, that we’re now spending more time analyzing and finding meaning in it than

making decisions and testing from it. This is the Big Data phenomenon called

analysis paralysis.



IDENTIFYING AN ITOA SOLUTION

The term IT Operations Analytics (ITOA) can be a deceiving one. Many software

solutions that call themselves an ITOA solution can actually only offer you half of

what you seek. Here it’s important to make the distinction between two types of

Operations Analytics and Intelligence tools: end-to-end vs. front-end solutions.

An end-to-end (or full-stack) solution is made up of a platform back-end, basically

the tools and algorithms that handles preparing all the data, and a front-end that

creates data visualizations and dashboard reporting.

While we like to see our data in easy to handle visualizations, platforms that only

give you this are not enough to get real insights from your company’s data. With data

visualization tools, as you can imagine from their name, you don’t have all the initial,

background stages of preparing and joining the data. This means that users need to

first have data that can be fed into the software, i.e. a pre-made central database.

Data visualizations are, just as their name implies, tools used to visualize data. This

means they do not handle all the preliminary stages of joining and preparing the

data – meaning, users need to work to make the data fit the software, rather than the

software works for them to make the data useable.

This cumbersome process can be avoided with an end-to-end solution as these

enable users to create complex formulas that work in separate sources. The software

automatically does all the necessary pre-calculations, allowing you to skip straight

ahead to the information you were after.



When it comes to enterprise needs, the difference between these two types of

software, are strikingly clear. It’s also clear that visualizations, though important,

cannot be the sole component of powerful Operations Analytics software.

If all you’re looking for is a beautiful report, then data visualization tools might work

for you. But when it comes down to the nitty gritty of data analysis, they are definitely

not enough. ITOA software that is end-to-end, and incorporates the a robust back-end

that can handle huge amounts of messy data is essential to most businesses these

days. Just don’t fall for the pretty face of tools that don’t have the necessary

back-end support.

5 COMMON TASKS - ITOA vs. VISUALIZATION TOOLS

Let’s further explore the differences between the two types of tools by highlighting

challenges in performing 5 common ITOA tasks in each type of tool:

1) Prepare

ITOA: Automate Data Preparation in a Single Location

Issues with data quality means work must be done to prepare data in order to create

an accurate, complete and central version of the organization’s truth.

Data preparation can actually take up to 80% of the time devoted to analytics

projects, so shortening data preparation can obviously be a major time and

resource-saver.

Visualization Tools: No Data Preparation



Visualization tools lack data preparation capabilities, especially for complex tasks

and when the data is coming from disparate and often disorganized sources. This

means either having to repeat the same preparation work every time you add new

data or investing in 3rd party software for professional DBAs. As a result, a huge

amount of time and resources are devoted to data preparation before you can even

start to analyze it, or parts of the use cases are compromised.

AI Joe by Loom Systems: Patent-Pending Data Preparation Solution

AI Joe takes data preparation to the next level: a zero-touch approach which

identifies and prepares all the data for immediate consumption by the user

completely automatically. Where once 80% of attention once went, those 80% can

now be directed towards the next 4 tasks, and beyond.

2) Join

ITOA: Joining Sources

Working with different data sources requires connecting data together, preferably by

using a join. As most organizations don’t collect their data from one single source

and instead use a variety of sources (Excel, Salesforce, Google Analytics, etc.), joining

data is a crucial element of any modern ITOA solution.

Visualization Tools: Blending Sources

Visualization software relies on blending data in order to join data sources. The

problem is this method aggregates data and reduces the level of detail, thereby

limiting the ability to explore and perform calculations on a granular level. This

means some data stays ‘out of the picture’ and prevents posing ad-hoc questions

when analyzing different data sources.



AI Joe by Loom Systems: Automatic Correlation

By leveraging the ever-expanding computational power at IT departments’ disposal,

AI Joe can correlate all the information steaming in seamlessly and automatically.

AI Joe users don’t need to join data manually, or settle for inferior blended data.

3) Analyze

ITOA: Perform Complex Calculations

For analysis purposes, users often need to create formulas that perform several

calculations simultaneously and output results on a granular or summary level of

detail.

Visualization Tools: Pre-Aggregated Data

Visualization tools, which are focused on reporting, use a restrictive engine that

limits the number of aggregations per formula, often to a single aggregation. Hence

if more than one aggregation is performed in a calculation manual work needs to be

done to aggregate data beforehand.

AI Joe by Loom Systems: Measure-All

AI Joe’s Measure-All method for application monitoring and predictive maintenance

is just what it sounds like. There is no need to make painful decision about what

information goes into the system with AI Joe; it measures all.

4) Scale

ITOA: Grow to Many Users, Data Sources & Dashboards

Under the safe assumption that your data is going to grow much larger over time,

ITOA software needs to be scalable, i.e. to be able to query a larger number of records



and many fields simultaneously, as well as handle a larger amount of concurrent

queries without compromising performance. This is also an issue in larger

organizations where successful implementation of a ITOA project might garner

further interest by additional departments and users.

Visualization Tools: Problematic Scaling

Visualization tools have limited data processing capabilities, as their design is

focused on presenting existing data in graphical dashboards. Instead, they often

combine and load all data into the memory of the local machine to achieve

reasonable performance. This demands lots of RAM, which is expensive and quickly

leads to a degradation in speed, additional software and hardware costs or complex

performance tuning.

AI Joe by Loom Systems: Touchless Configuration Translates to Scalability

AI Joe’s touchless configuration and modest system requirements mean that it can

scale along with IT’s needs, without becoming a pain-point for growing companies.

5) Collaborate

ITOA: Share a Single Version of the Truth

Data must be updated to account for changes. If these updates are left to one single

factor within the organization (such as the IT department), a bottleneck soon forms.

ITOA software should allow different elements within the organization to change

existing datasets according to developments in their respective departments.

Visualization Tools: Segmented Collaboration

Visualization tools rely on updating de-centralized, separate data extracts which

easily fall out of sync when collaborating. Editing extracts is done locally on the user



machine, requiring sufficient computing power and creating a confusing

environment where each users has to understand and manage countless extracts.

Data stored in de-centralized data silos limits your ability to see a broader view of

the organization. And this segmentation means that the more users accessing the

data, the more error-prone the system becomes.

AI Joe by Loom Systems: The Ultimate ITOA Solution

As it allows all elements within an organization to access, change, monitor and

respond to the insights provided according to developments in their respective

departments, and along with its outspoken dedication to simple UI and

comprehensible data presentation, AI Joe fits the bill as the ultimate collaborative

ITOA tool.

Learn more about Loom Systems’ ITOA solution on

www.loomsystems.com




IT Operations Analytics vs. Data Visualization Tools

Software

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