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Rudderite featured on Microsoft Power BI Data Stories Gallery

Rudderite featured on Microsoft Power BI Data Stories Gallery

Congratulations to our data-storyteller Ketan Deshpande for getting featured on Microsoft Power BI Data Stories Gallery and earning much-deserved appreciation from the Microsoft Power BI community.

These entries were judged by the Microsoft Data Journalism Team, and the featured stories were selected for telling a compelling story, being original and creative, and effectively using Microsoft Power BI.

Rudder Analytics ranked highly in Top Indian IT Services

Rudder Analytics ranked highly in Top Indian IT Services

In this age of data, all business decisions are backed by analyzing data scientifically and Rudder Analytics has been helping businesses in all aspects of analytics.

It has been one and a half year since we started operations and we have already received rave reviews for our quality services. Rudder Analytics was recently ranked highly in the press release of IT Services review by Clutch.co.

Clutch, an independent ratings and reviews site based in Washington, D.C. that covers top companies in IT services, awarded us at Rudder Analytics earlier this month a distinction as being one of the top companies in its research and thus a place in its India IT Services Leaders Matrix.

Our focus on niche categories of IT services from our basket of visual analytics with Tableau, Qliksense, Power BI etc., data analytics and statistical modeling services, along with strong praise from past clients earned us the compliment. For example, consider the all 5-star rating from one of our clients and their report that: “Rudder Analytics was able to provide that extra kick.”

We are really pleased to receive any feedback from our clients but especially happy to see a very satisfied customer – it means we have done our job and done it well. Thank you to everyone who has participated in the review process. Please take a minute to see our Rudder Analytics coverage in full.

Rudder Analytics got featured on CNBC as one of the leading IT services firms in India


Rudder Analytics got featured on CNBC as one of the leading IT services firms in India.



Rudder Analytics has been featured on CNBC as one of the leading IT services firms in India and this is what the analysts had to say about us:
“These companies are the finest examples of outsourced IT services firms in India based on our current book of research,” said Clutch analyst Clayton Kenerson. “All of these companies should be proud of their clients’ reviews – the proof of their professionalism and technical prowess that lends them hard-earned distinction in an otherwise crowded market.”

http://www.cnbc.com/2016/09/08/pr-newswire-clutch-recognizes-leading-it-services-firms-in-india.html

Will QuickSight Kill Tableau ?

QuicksightOver the past years we have seen an exponential increase in the amount of data being generated. On an average, nearly 2.5 quintillion bytes of data was being generated every day in 2012. Extracting actionable insights from such prodigious amount of data can be a nearly impossible task at times.

Gartner 2015 MQ

Fig 1: Gartner: Magic Quadrant for Cloud Infrastructure as a Service, Worldwide report, Lydia Leong et al, published 18 May, 2015

Amazon Web Services has been one of the pioneers in catering to the ever-changing data needs of enterprises with its highly scalable and pay-as-you-use services.

AWS senior vice-president, Andy Jassy recently unveiled QuickSight, a brand new service from AWS in Business Intelligence domain, during an annual re-invent conference held for developers. Some of its salient features are

  • Extremely fast, cloud-powered, BI service for 1/10th the cost of traditional BI software.
  • Fast Calculation with in-built SPICE (Super-fast, Parallel, In-memory Calculation Engine)
  • Easily scalable with thousands of customers and terabytes of data.
  • Provides SQL-like interface for other BI Tools to access data stored in SPICE.
bdt319-new-amazon-quicksight-cloudnative-business-intelligence-17-638

Fig 2: Working module of Amazon QuickSight (aws.amazon.com/quicksight/)

Most of the organizations using traditional BI solutions (SAP Business Objects/Crystal Reports, IBM Cognos, Oracle BI etc.) invest in substantial resources to get their first visualization. Agile BI solutions (Tableau, Qliksense, Sisense, Domo etc.) have their own constraints in terms of processing and customization capability, which limit their potential use.

Bearing in mind all these aspects, we need to ask, “Can Amazon QuickSight really kill the old guard BI services?” Let us take a look at some of the many crucial characteristics that we can consider to compare Amazon QuickSight with the market leader in BI services i.e., Tableau.

QUICKSIGHT v/s TABLEAU

Price: 

Amazon QuickSight has come up with an extremely competitive pricing structure (90% less as compared to other BI products). Its standard edition is priced at $9 per month per user and the enterprise edition is priced at as low as $18 per month per user (one year contractual basis).

Pricing

Fig 3: Pricing Structure for Amazon QuickSight (aws.amazon.com/quicksight/)

Tableau on the other hand has its cloud-based service (Tableau Online) starting at $500 per user per year. This gives QuickSight a huge edge over other competitors, especially while catering to small to medium enterprises, which are sensitive on budget.

Data Processing:

One of the major features of Amazon QuickSight is SPICE- a Super-fast, Parallel, In-memory Calculation Engine. Based on the technique of columnar storage coupled with in-memory technologies, SPICE helps in running queries at a lightning rate producing results in a few milliseconds with following salient features:

  • 2 to 4x compression columnar data
  • Compiled queries with machine code generation
  • Rich calculations and SQL-like syntax

For the data to be analyzed using QuickSight it is mandatory for the data to be in SPICE. This enables organizations to scale their data to large volume without any additional overhead.

Tableau’s Data Engine is an in memory analytics, high-performing database on one’s PC. It uses memory mapped I/O, i.e. the data is loaded in disks after it is imported. This results in low usage of RAM which eventually provides the desired performance.

Target Group:

Both Amazon and Tableau, have a significant customer base ranging from small scale organizations to some of the top firms in the world. Nevertheless, AWS has been a promising player in providing customer satisfaction, as a result of which most of the organizations tend to use AWS for storing massive data. It makes sense here to say that Amazon will target its AWS users as potential customers for QuickSight. Many organizations are shifting their base from on-premise to AWS Cloud for several reasons. On the contrary, some enterprises still prefer to store their critical datasets on their local premise for legal and security reasons.

Ease of Use:

Amazon posits QuickSight as a self-discovery tool which does not require people to have in-depth knowledge about data visualization. Tableau on the other hand requires certain level of expertise.

Features:

Finding the right visualization for data is extremely important. QuickSight’s Autograph feature automatically predicts the best visual for your data to be displayed. Likewise, Tableau provides us with a “Show Me” which detects data based on data types, cardinality etc.

Limitations:

QuickSight is most appropriate for data that is stored in AWS’s cloud and also more importantly the data that can be put onboard SPICE. As quoted by Ashley Jaschke (Director, Product Management, Tableau) QuickSight will be suitable for lightweight visualizations. Many companies still keep their data outside of AWS’s cloud. Since, Tableau has a provision for ingesting data from multiple sources it has the ability to provide much deeper and significant insights.

QuickSight is currently available only as a preview version and it would be too early to decide as to whether QuickSight will dominate the BI services market, but it is surely poised to make a heavy impact.

Two Way Synchronization between Google Spreadsheet and AWS RDS using Google Apps Script

sheets logoGoogle Spreadsheet can be a very nifty tool to satisfy dynamic data storage needs for any small to medium data analytics projects. Using Google Apps Script, Google Spreadsheet can fetch data from any RESTful API and act as an easily editable data source.

Google Spreadsheet can be directly used as a data source to most of the major analytical dashboard platforms like Tableau as well as operational dashboard platforms like Klipfolio. However, connectivity from Google Spreadsheet to Tableau is not perfectly stable yet and may run into issues on Tableau Server.

One way of getting a more robust method of connectivity from Tableau to Google Spreadsheet could be using an intermediate layer of RDS Database services of AWS. In Google Apps Script, the JDBC service supports, as standard, the Google Cloud SQL, MySQL, Microsoft SQL Server, and Oracle databases.
In this blog, we show you a step-by-step synchronization process of connecting Google Spreadsheet with Amazon’s RDS Web Service. We should bear in mind that Google Apps Script still does not provide connectivity to PostgreSQL DB.

Step 1: 

To demonstrate we have some dummy data on the Spreadsheet(Insights_Summary_Spreadsheet is the name of this Google Spreadsheet) which is extracted using RESTful APIs.

sheet

Step 2:  

This data needs to be moved to the database on cloud (AWS RDS MySQL instance). So, the next step involves setting up an RDS MySQL instance on AWS. After having setup the basic RDS MySQL instance, we need to whitelist a few IP addresses to allow Google Apps Script to access your database. Following are the address ranges you’ll need to whitelist:


  64.18.0.0 - 64.18.15.255
  64.233.160.0 - 64.233.191.255
  66.102.0.0 - 66.102.15.255
  66.249.80.0 - 66.249.95.255
  72.14.192.0 - 72.14.255.255
  74.125.0.0 - 74.125.255.255
  173.194.0.0 - 173.194.255.255
  207.126.144.0 - 207.126.159.255
  209.85.128.0 - 209.85.255.255
  216.239.32.0 - 216.239.63.255

Note: JDBC Service does not connect to port lower than 1025. So make sure that you are not allocating a lower port. 

To add the above IPs to the security group, select the RDS instance and then Edit the Inbound section. Add Rule(IPs) as per requirement. Once this is done, you are ready with your RDS instance to work with Google Apps Script.

RDS

rds2

Step 3:

In this step we fetch data from Google Spreadsheet into RDS. We need to make a connection to the RDS instance using JDBC Service. In the Google Apps Script project we build the following code.

// Replace the variables in this block with real values.
 var address = 'database_IP_address'; //End point provided by the RDS Instance
 var rootPwd = 'root_password'; //Root password given while configuring DB instance
 var user = 'user_name'; //Username given while configuring DB instance
 var userPwd = 'user_password'; //User password given while configuring DB instance
 var db = 'database_name'; //Database name to which you want to connect
 
 var dbUrl  = 'jdbc:mysql://' + address + '/' + db; //Generates the database url to which you can connect to
 var conn = Jdbc.getConnection(dbUrl, user, userPwd);

Next, we build the code to select the spreadsheet from where we need to fetch the data. 

 var ss = SpreadsheetApp.getActiveSpreadsheet(); /* This represents the whole data */
 var sheet = ss.getSheetByName('Insights_Summary_Spreadsheet'); /* Replace with your own spreadsheet name */
 var range = sheet.getRange();   /* This represents the whole data */
 var values = range.getValues();

Then using prepare statement we can insert data into RDS.

/* Query to insert fields into the table on RDS. Here Insights_Summary_RDS is the table created in RDS. */
var stmt = conn. prepareStatement('INSERT INTO Insights_Summary_RDS(date,clicks,costs,ctr,cpc,impressions,cpm,avg_pos,budget)values(?,?,?,?,?,?,?,?,?)');
stmt.execute();

code

Step 4:

In this process we fetch data from RDS to Google Spreadsheet if required by our project. After establishing the Google Spreadsheet to RDS connection as shown previously, we build the following code:

var stmt = conn.createStatement();
var store_results = stmt.executeQuery('SELECT * FROM Insights_Summary_RDS');

The data returned from the query is stored in a variable called store_results. Now we need to write the records by using a looping structure until the end of the data in the store_results.

while (store_results.next()) {
 var rowString = ' ';
 for (var column = 0; column < numCols; column++) {
     rowString += store_results.getString(col + 1) + '\t';
     }
 }
 store_results.close();
 stmt.close();

Eventually a simple Google Apps Script can help us build a great analytical dashboard to get enhanced insights from the data.

Tableau for iPad: Project Elastic, Vizable and the unmet need for an equivalent of Tableau Reader app for iPad

^94CC986F1AB58484387E60ECE71B490D88170B70C1E1680390^pimgpsh_fullsize_distrTableau Software (NYSE: DATA) helps anyone quickly analyze, visualize and share information and boasts of helping more than 35,000 customers obtain visual intelligence in the office and on-the-go.

Portability, scalability, ease of development and cloud based hosting are a few of the major concerns that fast paced organizations have to deal with while buying BI tools. Although iPad is the most popular portable device in the business industry, not much has been offered in this segment by major BI platforms.

In October 2015, Tableau released the app ‘Vizable‘ for iPad (earlier codenamed ‘Project Elastic’ during R&D phase). Vizable aids in understanding data patterns and their relationships. It is a fast paced powerful tool which shows trends and graphs, converting data into information.

Having said that, there are many basic features yet to be added to Vizable.

  • At present, Vizable has no option available for developing any module, restraining itself to only playing around with filters, adding columns, sorting, etc.
  • Considering the visual components available, bar chart for data in categories and a line chart for data by time are the only options Vizable currently provides.
  • Data files can only be opened if they are stored on the iCloud.In the same segment, Tableau has also introduced a new app named Tableau Mobile to stay in touch with data whether you are offline or online using the live Tableau Server or Tableau Online connections. This app too, has its drawbacks at a certain level. The best use of Tableau Mobile can be seen only if we are connected to the server. However, when offline, Tableau Mobile provides only snapshots view of the dashboards.

QlikView and Spotfire are the two other bigwigs in the visual analytics industry which have their own apps competing with Tableau Mobile and Tableau Vizable. The following chart provides a brief comparison amongst the three.

CRITERIA QLIKVIEW MOBILE SPOTFIRE ANALYTICS TABLEAU VIZABLE
Cost Free Free Free
Rating Low Low High
App Size Light (7.5 MB) Light (5.3 MB) Heavy (70.9 MB)
UI Complex Simple Very Simple
Offline Usability Yes No Yes

In this segment, there is no sole winner yet as each of the above has their pros and cons. However, as far as the statistics are concerned, Tableau is leading the industry with an annual growth rate of 114% and operating in more than 150 countries. In spite of this, it leaves a lot to be desired when it comes to the need of a portable solution.

5 Features Klipfolio Must Have

5 Features Klipfolio Must Have

5 Features Klipfolio Must Have

Klipfolio is an online dashboard platform and is widely used for building real-time business dashboards. The company was founded by Peter Matthews (present CXO) and Allan Wille (present CEO) in 2001 and is headquartered in Ottawa, Canada. The company has focused on creating an operational browser based dashboarding product with ease in usability for non-technical users.

With its rich dashboard features and data integration capability with various data services, it is arguably one of the best cloud based platform in its price range. Some of the key dashboard development features are user role management, custom CSS, data refresh scheduling, user annotations and powerful data manipulation capability. The other competitors are Cyfe, Geckoboard, Ducksboard etc but Klipfolio is still winning over them in most of the product features.

Despite of being a fan of this platform, today I am going to succinctly pin-point 5 features Klipfolio must include in near future.

  • Multiple Select Input Control

The input control component klip (term given by Klipfolio to its widgets) currently allows users to select from 3 input options – Dropdown Selection, Text Input and Date Picker. All these controls are typically used for filtering the data in klips. The dropdown selector let you select only single item to filter the data which sometimes limit user’s view.

  • Scaling Map Visualization

Map visualization is an interesting feature of Klipfolio. However, this feature is limited for selected geographies in world like USA, Europe, Germany etc. Adding more geography would certainly make this feature more useful.

  • Better Data Handling

Klipfolio can only handle data up to 10MB size. Once the data source size increases, the dashboard load times starts getting affected.

  • Drill Down Capability

Klipfolio has minimalistic drill down capability. With the current architecture, it is unlikely to see major improvements in near future.

  • Calculated Data Fields

Data manipulation can currently be done only by using functions inside a klip. These functions are great and can take care of almost all the data manipulation requirements but at the same time affects the performance. Having an option to add calculated fields would not only help in easing the calculations but will also improve the dashboard load time.

 

With all said, Klipfolio is still a great platform for SMEs and the product development team is well aware of all its shortcomings!

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