Create A Custom Table Report using Helical Insight (Dynamically Picking the Columns Names and Data)

Create A Custom Table Report using HI (Dynamically Picking the Columns Names and Data)

If you have already had a Hands-On experience on the Helical Insight Tool [HI tool] then this blog would be helpful

For a creating a report there are 4 files required
1. EFW
2. HTML
3. EFWD
4. EFWVF

the Report Layout lies on the HTML page, the SQL queries lies within the EFWD file and the visualization lies in the EFWVF File.
Hence once the Query is fired it comes to the visualization file to create a table as that’s our goal. With the help of the following code below it can be created with ease.

The below code here is a template of our EFWVF looks like
<Charts>
<Chart id=”1″>
<prop>
<name>Table</name>
<type>Custom</type>
<DataSource>1</DataSource>
<script>

//Your Visualization Code Goes Here

</script>
</prop>
</Chart>
</Charts>

Chart ID here is 1 which is unique
Type is of custom
DataSource 1 is the Unique ID defined in the EFWVF File. ie (<DataMap id=”1″ )
Now within the <script> </script>
we Paste the following:

<![CDATA[
//The If Block Does Return A Message NO Data when there is No Data
if(data.length == 0)
{
$(‘#chart_1′).html(“<div ><h4 style=’text-align:CENTER;color:black; padding-top:60px;’>No Data Available For Current Selection</h4></div>”);
return;
}
//The Else Block Returns The Table if there is a Table
else
{
//Here the funtion Tabluate Returns the Data in Tabular Form
function tabulate(elem, data, columns)
//Function Start
{
var table = d3.select(elem).append(“table”)
.attr(“class”,” table display compact width:100%;cellspacing:1 “)
.attr(“id”,”table”)
thead = table.append(“thead”),
tbody = table.append(“tbody”);

//Append the header row
thead.append(“tr”)
.selectAll(“th”)
.data(columns)
.enter()
.append(“th”)
.text(function(column) { return column; })
.attr(‘class’, function(d, i){ return “colH_” + i; })
.style(‘background-color’,’#ededed’)
.style(‘color’,’black’)
.style(‘@media print’,’display:none’)
.style(‘padding-left’,’25px’);

// create a row for each object in the data
var rows = tbody.selectAll(“tr”)
.data(data)
.enter()
.append(“tr”);

// create a cell in each row for each column
var cells = rows.selectAll(“td”)
.data(function(row) {
return columns.map(function(column) {
return {column: column, value: row[column]};
});
})
.enter()
.append(“td”)
.text(function(d) { return d.value; })
.attr(‘class’, function(d, i){ return “col_” + i; })
.attr(‘align’, ‘left’)
return table;
//Function END
}

//Render the table
//Object.keys(data[0]) is the Data to fetch the Column Header
//data has the data of the Table
console.log(Object.keys(data[0]));
var subjectTable = tabulate( ‘#chart_1’, data, Object.keys(data[0]));
}
]]>
Save it in the same Directory with rest of the file

Run your report on HI and you get a table.

Keep in mind you can change the query and still get the new columns from the new query.

Thanks
Sohail Izebhijie

Beginner’s Guide to E.T.L (Extract, Transform and Load) – Introduction

Introduction into E.T.L (Extract, Transform and Load)
This a process related to data warehousing which involves the extracting of data out of the source system/Systems
and placing it into a repository or Target.

Extraction
Extracting the data from source systems (Flat Files or other operational systems) and converted into one consolidated data warehouse format which is ready for transformation.

Transformation
Transforming the data may involve the following tasks:

  • Cleaning: One of many very important task in the transforming stage because the Source data would always have data that the target system doesn’t support or understand hence cleaning is required.
    In some cases the Source can be from many source inputs so Lookup are important to avoid duplication.
  • Filtering: Now the Source Data would have so many rows but it’s important to send relevant data to your target and  filter out the unnecessary data.
  • Business Rules: Calculations or Derivations can be performed Here so we can have Correct and readable data at the target.

and many more.

Loading

After proper transformation and data matches the Business Rules loading the data into a target or repository is the final step in the E.T.L (Extract, Transform and Load)

in my next blog we will look into the basic Loading Data from Source to Target

Thanks
Sohail Izebhijie

Importance of Business Intelligence in Travel Industry

Importance of Business Intelligence in Travel Industry

 

The travel industry is highly complex with multiple players and systems interacting with each other on real time basis for smooth functioning of the business. The various players and systems include Travel Management Companies, Global Distribution System Providers, Call Centers, Travel Agencies, etc. Due to these complex systems, a huge amount of data is generated continuously. But, there are big voids in data collection and this poses as a big challenge for the travel industry. Travel companies are hence finding it very difficult to run targeted campaigns; they are neither unable to offer personalized products to customers nor utilize Predictive Analytics. However, introduction of new technologies is slowly changing the way travel organizations collect and use data.

         Business Intelligence and Analytics play a key role in addressing many revenue impacting and operational inefficiencies. When the data is combined with multiple external sources like data from travel companies, online portals, private websites and from social media, the intelligence obtained is significantly gives greater insights into customer behavior patterns. Such kinds of insights help organizations analyze trends and customer preferences – their likes & dislikes and sentiments. This would then act as an extremely powerful tool for devising business strategies and discovering hidden sales opportunities.

For example, when an Airline route suddenly starts showing negative revenues while operating which has always been profitable before, Business Analytics is capable of providing insights. Data from travel companies may reveal increased competition in the sector. Online portals like Ibibo, MakemyTrip will provide data in the form of user comments and blogs, which when analyzed, can provide results from sentiment analysis. It can reveal the brand equity and impression that customers have about the organization. If the outcomes are not favorable, organizations can put in extra efforts to analyze the reasons behind it and devise an improvement plan. The processed data can also be presented in the form of reporting dashboards showing factors affecting customer sentiments.

Predictive Analytics in Travel

Suppose a person is travelling for an International Vacation to Singapore. He booked his tickets using one of the online portals like MakeMyTrip. Thanks to the power of predictive analytics, the person might receive an exclusive offer from his favorite airline for the ideal route along with an option to include a hotel and perhaps best restaurants in Singapore for someone traveling on an expense account.

KPIs for Travel Industry

The following are the most generic and key categories for Travel Organizations:

  • Spend and Savings :  Spend Under Contract, Booking Visibility, Payment Visibility, Reaalized Negotiated Savings, Contract Competitiveness, Cost of Managed Travel.
  • Traveler’s Behavior and Policy : Cabin Non-compliance, Lowest Logical Airfare (LLA) Non-compliance, Advance Booking Non-compliance, Online Adoption Rate, Hotel Visibility, Hotel Quality.
  • Suppliers : Traveler Satisfaction, Contract Support
  • Process : Re-booking Rate, Reimbursement Days
  • Traveler’s Safety : Location Insights, Profile Competition
  • Corporate Social Responsibility (CSR) : Carbon Visibility, Rail vs Air
  • Data Quality : Data Quality

 

Benefits of Using BI in Travel Industry

  • Enhance customer segmentation
  • Increase revenue
  • Targeted offers and promotions
  • Benchmark against industry standards
  • Reduce operational cost
  • Competitor insights
  • Increase inventory utilization
  • Improve customer service

 

Some of the other areas where BI can be applied to Travel Industry are

  • Capacity Planning
  • Transporters Performance Evaluation
  • Mode-Cost Analysis
  • Supplier Compliance Analysis
  • Routing and Scheduling
  • Driver Performance Analysis

 

A Travel Domain company “CTI Travel Ltd” had implemented business intelligence in their system. This upgraded system had benefited them in various ways like :

  • Real time tracking on supplier
  • Sales team got benefited in finding new business leads, profitable and under-performing clients.
  • Improved client experience and customer centric services
  • Helped in finding the gaps using the real time data
  • High quality Reports using real time data
  • Better Financial Management
  • Improved complicated processes
  • Improved decision making processes by management / teams / individuals

 

With rich experience in various domains including travel (empowering travel management software of IBNTech) get in touch with us at Helical IT to find out more about how a BI solution can benefit your company. Reach out to us at nikhilesh@helicaltech.com