Data Science & Analytics using Periscope Analytics (Sisense) Simplified
It’s a well-known fact that organizations these days work on voluminous data. And often, managing this data can be a tedious task. However, with the help of proper tools, you can not only parse this data but can also uncover the correct information as well.
Table of Contents
Data Science and Data Analysis have become an integral part of Business Intelligence. And to study the productivity of your business, you need to understand the uniqueness of each data point. But before that, you need to have a better understanding of Data Science and Data Analytics.
In this article, we will discuss Data Science and Data Analysis and how Periscope Analytics/Sisense helps simplify the data.
Table of Contents
- Introduction to Data Science
- Introduction to Data Analysis
- Difference between Data Science and Data Analysis
- Introduction to Periscope Analytics (Sisense)
- Setting up Periscope Analytics (Sisense)
- Understanding the Need of Periscope Analytics (Sisense)
- Key Benefits of the Periscope Analytics (Sisense) Platform
- Visualizations Supported by Periscope Analytics (Sisense) for Analytics
- Building Dashboards in Periscope Analytics (Sisense)
Introduction to Data Science
Data Science focuses on finding answers to questions that one does not know even exists. It takes into consideration large sets of raw and Unstructured Data. The experts use different techniques like Predictive Analysis, Statistics, Machine Learning, and more to parse massive datasets for solving complex business problems.
Introduction to Data Analysis
Data Analytics, on the other hand, is the Statistical Analysis of existing datasets. The main focus here is to find solutions to business problems for better decision-making. The result, thus obtained, can be immediately sent for improvement. Data Analytics focuses on some specific regions having specific goals.
Difference between Data Science and Data Analysis
Often, people think Data Science and Data Analysis fundamentally represent and involve the same process. However, this is not true. There is a slight difference between Data Science and Data Analysis, but both are said to be the different sides of the same coin.
Data Science is a broad concept that deals with massive sets of data, while Data Analysis is a part of Data Science.
How these two leverage datasets, is what makes them different. Data Science deals with the construction and designing of new processes, including Prototypes, Algorithms, and Custom Analysis. Businesses use Data Analysis to create a better strategy by examining a large set of data. Thus, it is more specific and concentrated than Data Science.
Introduction to Periscope Analytics (Sisense)
Periscope Analytics/Sisense simplifies complex data and makes Business Analytics easier. Backed by the power of unique In-Chip and Single Stack Technologies, Periscope Analytics helps deliver unrivalled performance, agility, and value by eliminating the significant cost required for Business Analytics tools.
Instead, it provides a single, complete tool to analyze and visualize large datasets without IT resources. Having more than one thousand customers in 50 different countries, including global brands, Periscope Analytics has bagged many awards and recognitions.
For further information on Periscope Analytics/Sisense, check the official website here.
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Setting up Periscope Analytics (Sisense)
The setup of Periscope Analytics/Sisense can be done in many ways depending upon your need and preference. For example, you can either set it up as a Single Node or Multi-Node Linux or deploy it on Windows or any Cloud environment.
Sisense on Linux is built on microservices architecture whereas, on Windows, it can be installed using UI-based Sisense Installer. In addition, you can use Sisense through Sisense Managed Services.
Once installed, you can connect it in two ways:
- Designers here can directly connect to Cloud Data Warehouses like Amazon Redshift. In addition, you can run the queries directly against the underlying Data Store.
- The second option allows you to pull data from any Data Source within a single data model.
Understanding the Need of Periscope Analytics (Sisense)
Blending data in a consumable fashion is a bit risky for organizations. As a Data Engineer, your job revolves around providing complex data from multiple sources or performing Advanced Analysis to achieve specific goals.
To achieve the goals, you need some quick way to store such massive amounts of data and employ relevant Data for Analysis. This is why you need a platform that can make the job easy for you. With the powerful tools offered by Sisense, managing data has become convenient for organizations.
Seeing the complexity of data, organizations these days need a more advanced approach to Data Analysis while ensuring the rapid development of their business. This includes proper planning of the data capabilities, right from building a Data Pipeline to self-service BI tools and more. Sisense helps exactly with this by providing powerful tools for simplifying complex data, building data products, and delivering insights for both the inside and outside of the organizations.
Periscope Analytics/Sisense is an AWS Partner Network that works in collaboration with AWS Data & Analytics Competency to provide services like Amazon Redshift, Amazon Simple Storage Service, Amazon Athena, Amazon Relational Database Services.
Sisense requires less or no involvement in the IT environment and is used by businesses to build Interactive Dashboards.
Key Benefits of the Periscope Analytics (Sisense) Platform
Although we have discussed how Periscope Analytics helps businesses, still let’s talk about its benefits in this section:
- With Sisense, the process of decision-making is enhanced that further helps in increasing profit and improving efficiency.
- The Predictive Analysis feature here helps businesses to plan better for the future that previously was impossible to achieve.
- It helps organizations make informed decisions.
- There is little room for guesswork because of past experiences.
- The clear datasets support accurate decision-making.
1) AI-Driven Analytics Features of Periscope Analytics (Sisense)
Sisense employs an AI Algorithm that runs in the background and scans the entire dashboard associated with a particular data model. This Algorithm studies the pattern and behavior of all dashboard users.
With time, the Algorithm picks up more input from user activity and shows more accurate results targeted as per the user’s needs.
2) Periscope Analytics’ (Sisense) Embedded Analytics Support
Sisense’s Embedded Analytics is an end-to-end solution that is integrated within your application. It lets your customer easily prepare, analyze and visualize complex data.
Sisense’s Embedded Analytics lets you accomplish the following goals:
- It helps you integrate Sisense with your current interface & branding.
- Managing, reporting, and visualizing data becomes easier.
- Sisense’s Embedded Analytics also helps you integrate SSO and Active Directory.
- It takes care of your Data Security as well.
Sisense’s Embedded Analytics is mainly for product managers and developers.
Visualizations Supported by Periscope Analytics (Sisense) for Analytics
Sisense supports either static or interactive data visualization. In static visualization, users can have a single view of what’s in front of them while interactive visualization enables users to view different forms of the same datasets selecting any particular dataset.
Have a look at the various types of visualisations supported by Sisense:
- Indicators: This is a simple Gauge Indicator that shows whether you are moving in the right direction or not.
- Line Charts: These are great for showing the relationships between data points. Mostly, they are used to show any change or trend over a certain period.
- Bar Charts: Bar Charts are meant to compare the quantities of different categories or items.
- Pie and Donut Charts: These are used to check how different parts of a whole compare to each other.
- Area Charts: These are used to have a deeper insight into resource and financial planning and allocation.
- Pivot Tables: Here you can compare the entries with the exact figures. These are mostly used to do a comparison of the components of the same category.
- Scatter Charts/Maps: When you have numerous data points, you can use Scatter Charts to correlate them.
- Bubble Charts: These are the same as Scatter Charts, the only difference is that these have bubbles in place of markers or dots to correlate the data.
- Heat Maps: Heat Maps are useful when there is only one data point having a wide value. With Heat Maps, the opportunities can be easily pinpointed.
- Tree Maps: Here, colour-coded rectangles are put inside or next to each other. These can be used to compare the value between and within categories.
- Polar Charts: These are also known as Summary Resource Grade Charts. They act just like a Pie Chart.
- Funnel charts: These are used to show the decreasing value of the sales funnel when customers move through it. Here, conversion rates can be easily viewed at each step. So, you have an idea where you are losing people.
Building Dashboards in Periscope Analytics (Sisense)
Sisense helps you create a dashboard in two ways- the first is through the Sisense Analytics page and the second is through Sisense Rest API.
The difference between both methods is that the Analytics page provides you with an interface where you can put different widgets in the Dashboard.
1) Creating Dashboards through Analytics Page
Step 1: On the Analytics page, click on “+” above the Dashboard list or Right-click on the folder menu and select “New Dashboard”.
Step 2: A window will appear. In the displayed window, click on the Data Set on which you want to work.
Step 3: Enter a title to create a name for the Dashboard.
Step 4: This name appears at the top of the Dashboard list.
Step 5: Finally, click on “Create”. You will then be automatically guided through the process of creating your first Widget in the Widget Wizard.
2) Creating Dashboards through Periscope Analytics (Sisense) Rest API
Step 1: In Sisense, click on “Admin” at the top. After that click on “Rest API”.
Step 2: Next, select Version 1.0 on the top right of the screen.
Step 3: Click on “Dashboards” and then on POST/Dashboards.
Step 4: Define values for different calls as per the requirement.
Step 5: Lastly, click on “POST”. The Dashboard gets added to the Dashboard list on the Analytics Page.
Sisense is beneficial in simplifying end-to-end Data and Analytics, thereby reducing time to build advanced data models. It also offers an Automated Analysis of visualizing data of any size. Periscope Analytics/Sisense is a leading AI-driven Analytics platform that uses Business Intelligence to infuse data from anywhere & this is where Hevo saves the day.Visit our Website to Explore Hevo
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