Business Intelligence combined with Big Data analytics is stimulating the progress of Enterprises across the globe, along with pulling whooping amount of investment within the Big Data community. The infographic given below on big data in shaping everyday lives elucidates people about how Big Data is making our lives better.
When Moore’s Law meets with modern day Business Intelligence, what happens? Disruption and then wider adoption!
With costs of implementing BI tools lowering, more and more enterprises are keen on jumping on-board the homebrewed variety of custom BI solution to help drive their business. The result of these efforts is that these days several organizations are pursuing data driven intelligent decision-making, at a cost, which is almost fractional compared to yesteryear’s Business Intelligence budgets.
A proper Big Data certification allows individuals to make the best of available smart BI solutions available out there!
But the question remains, as to are all these companies actually making better decisions?
Surely, most enterprises are now reaping the benefits of having a larger range of BI solutions available to them. Nevertheless, there is still a bigger room for error in the picture, which many firms tend to ignore.
If done right, BI solutions can deliver an ROI of USD 10.66 for the cost of every dollar spent on implementing them. But, as per a survey conducted by Gartner, the results are not so glorious for most firms. More than 70 percent of all BI implementations do not stand up to meet the business goals that were anticipated of them.
Due to the evolution and lowering BI solution prices, the demand for data analytics certification courses have grown by several manifolds.
Is there a secret formula to BI solution driven success? Well, starting with asking the right questions is always a good place to begin:
Do you know what the lifeblood is for BI? Why, data of course, data is what Business Intelligence strives upon. All firms do have a rudimentary strategy to collect and analyze data, however, they tend to overlook the data sources. The key here to note is – truly reliable data sources are the main difference between the success and failure of your Business Intelligence efforts.
These data sources do exist; all you have to do is choose right. In addition, the best thing about them is a lot of them are almost free of charge. Using the good ones will transform the way you look at your market, the business pipeline and the way you perceive your audience.
These are your firm’s single source data repositories. Warehouses store all the data you collect from various sources, and provide the same for when needed, on prompt for reporting and analysis. However, self-service BI tools can be a bit of hit-or-miss at times, where consistently handling data is a worry.
The key is to discover a data warehouse solution, which can efficiently store, curate and retrieve data for analysis on prompt.
Companies that are looking to use their own Business Intelligence infrastructures must identify the analytics architecture that best suits their necessities. However, unwieldy datasets in combination with a lack of processing maturity can dull the effort even before one decides to start!
For incorporating enterprise-scale Business Intelligence solutions, it is necessary to have it work effortlessly with the different other information formats, processes and systems, which have already been established previously in the internal work pipeline.
So, the key here is to ask the question – will the necessary integration cost more in terms of resources and effort that you can afford?
The most persistent challenge in BI is to wrangle data, majority of users cannot understand any of it beyond a simplified visualization. Decision-makers may be fooled with the help of powerful visualization tools. However, the truth is that making it pretty alone will not get the job done right.
So, forget pretty, and ask the all important question of whether the reporting mechanism is useful in interpreting otherwise unintelligible data or not.
If your BI solutions, directly impinges on relevant regulations (and so it will, when the time comes). Then the solutions should aid the compliance and not hinder it. A good BI solution should provide a means to trace and audit data and its sources wherever, needed.
The field of data science is evolving in expertise. And even professionals involved in the field tend to vary in their capabilities and opinions about the same. So, the important thing is to consider the importance of data in your company, and that one has all the appropriate responses to the posed questions above.
You can learn to ask the right questions with comprehensive tableau BI training courses. For more information on tableau course details feel free to contact the experts at DexLab Analytics.
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Let us not waste any time on reading long-worded introductions, and get right down to our 5 top tips for creating different map styles in Tableau.
You will be able to find out about these tips and a lot more on Tableau with our Tableau training courses.
A simple way to create a clean map for best visualization is by removing the map layers. In order to do this, all you need to do is Select Map on the toolbar menu and “map layer”. Then simply click on the uncheck box and everything in the map layer window, this will leave behind only the outline of the map data.
Image Source: dataplusscience.com
Tableau course details has all these steps and much more to learn about the software, you can know the details by visiting our Tableau training institute website.
When you use map, you can change the border colours of the map under the option ‘Color’. Simply select the colour and choose the border colour that you desire.
Image Source: dataplusscience.com
Combining the above mentioned step 1 and 2 and by clicking to remove the fill colour, we can create an outline of a map. To do so, first remove the map layer shown in step 1 and then set the map fill colour to match with the background colour. And voila! After selecting the desirable colour for the borders (as shown in step 2) we now have created just a simple outline of the map of USA!
Image Source: dataplusscience.com
To do this in Tableau, you must remove the base layer which is similar as shown in the first step, we can then alter the Pane colour to change the colour of the water on the map to any colour we want. Once we get the base layer to be unchecked, all we have to do is simply right-click on the map and select ‘Format’ then select “Shading” and then alter the “Pane” colour to any shade of our choice.
Just like the previously discussed step (step 3) we can start by making the borders of the countries. In this case we have also combined the step 4 where the pane colour has been changed to match. This has given rise to a red coloured outline of the countries of the world on a pitch-black background.
Image Source: dataplusscience.com
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We are happy to announce that we have recently begun our corporate training sessions for the multinational company Jones Lang LaSalle Pvt. Ltd. on Tableau Business Intelligence.
The company JLL are a professional service where they deal with investment management firm offering specialization in real estate services for clients seeking increase in value by owning, investing and occupying real estate. It is a Fortune 500 company and gathers annual revenue of USD 5.2 billion with gross revenue of USD 6.0 billion. They have more than 280 corporate offices and operate in 80 countries or more, their global work force is of 60,000. The firm provides management and real estate outsourcing services for realty portfolio for its clients. Their portfolios consists of 4.0 billion square feet which is 372 million square meters and have completed USD 138 billion in sales, financial transactions, and acquisitions on 2015. Continue reading “We Are Providing Corporate Trainings To Jones Lang Lasalle Pvt. Ltd.”
Let us assume you have got sales data in your hands, wouldn’t it be absolutely grand to be able to recognize certain customer groups to be able to develop targeted marketing programs? It could also be that you are in healthcare and you’d love to identify patients who have had similar symptoms to determine the effectiveness of treatments.
With complex data these questions can be very difficult to answer, even when people have distinct and well-separated groups. Additionally, sometimes data is distributed in such a way that it contains no obvious gaps which can help us distinguish between groups with simple inspection. Continue reading “Now Easily Uncover Patterns in Your Data With Tableau 10’s Clustering Feature”
If you are looking to be hired as Tableau expert then you must be acquainted with these common interview questions and answers. These questions have been collected by the experts at DexLab Analytics who offer Tableau BI Certification training at the institute. These questions are to give you an idea of the types of questions you may be asked at an interview. Happy job hunting!
Data visualization is a much advanced, precise and ordered way of viewing large volumes of data. It is the way one visually represents data into graphs, charts and other illustrative aids, especially when you cannot define them textually. Through the various software applications like Tableau one can show various trends, patterns, correlations etc.
In Tableau desktop one can create workbooks for data visualizations but Tableau Servers are used to distribute the interactive workbooks or/and reports to the target audience. Users of Tableau servers can also edit and update workbooks and dashboards online on the Server but they cannot create new workbooks.
But there are limited options for editing in server as compared to desktop.
The differences in these two features actually lie in their applications. With parameters one can allow users to insert their values, which can be integers, dates, floats, string these can be used for calculation purposes. But in filters one can only receive values which the user chooses to ‘filter by’ in the list, this cannot be used to perform calculations.
In them users can change the measures and dimensions in case of parameters but for filters this feature is not approved.
Are you interested in a Tableau training course we can help you get a head start in this much coveted career. Simply view our course details at Dexlab Analytics.
Are You Trying to Ace Your Tableau Interview? from Infographics
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Tableau helps data analysts to visually analyze your big data and is a great tool that helps to solve complex problems associated with data analytics. By data visualization we mean, describing information through visual rendering to gather immediate insight with the mind’s powerful and quick visual processing system.
Earlier Tableau used to offer certification for version 8 both Desktop and Server. But now Tableau has released version 9 certification exams. Thus, now you can no longer register for the version 8. If you are already certified in version 8 of Tableau and would now like to upgrade yourself, you can sit for the 9th version delta examination with the new features only. Continue reading “Analysts’ Guide to Tableau Certification”
In the near future, the world’s data generation will nearly double in amount than what it is now. According to a survey conducted by the IDC (International Data Corporation) by 2020 we will generate 50 times more data than in 2011. Now that such a gargantuan amount of data will be generated which will come with real-world business implications, thus, businesses around the world will require tools which should be capable to analyze this data and gather actionable insights from them. Tableau is a tool that helps organizations do exactly that, i.e. data mining and visualizing business opportunities to take requisite actions for amplifying revenue generation. So, it is understandable that the demand for personnel proficient in Tableau is expected to rise by manifolds in the next few years.
So, we India’s leading Tableau training institute have compiled a list of the most commonly asked interview questions for a position of Tableau operator/executive in this post. If you have more such questions that you have recently come across in an interview and would like to know the answer feel free to drop them in the comments below and our data science training faculty will get to them ASAP. And if you would like to take up a Tableau Certification course or take up an online Tableau training check out our curriculum on Tableau BI Certification.
The best answer to this question: An ‘extract’ connection is a connection with a static database, which is refreshed every day/hour/period. In this case all data are copied from the data source to the Tableau Server. Refreshing the data source will not give you the latest data – you have to refresh the extract to get them.
A live connection will query the underlying data in the data source/database – refreshing the visualization will give you the latest results. In this case no data is copied to Tableau Server for pre-processing.
• Name a few of the different types of filters used in tableau.
The best answer to this question:
The 3 types of Filters in Tableau are:
1) Quick Filter
2) Data Source Filter
3) Context Filter
The best answer to this question: The difference actually lies in the application. Parameters allow users to insert their values these can be float, integers, string, date that can be used in calculations. However, filters receive only values users choose to ‘filter by’ the list this cannot be used to perform calculations.
Users can dynamically change measures and dimensions in parameter but filters do not support of this feature.
The best answer to this question: Viewing underlying SQL Queries in Tableau can be done in two ways:
• Create a Performance Recording, to register performance information about the main events you interact with workbook. Users can view the performance metrics in a workbook created by Tableau.
Help> Settings and Performance> Start Performance Recording
Help> Setting and Performance > Stop Performance Recording
• Reviewing the Tableau Desktop Logs located at C:\Users\\My Documents\My Tableau Repository. For live connection to data source, you can check log.txt and tabprotosrv.txt files. For an extract, check tdeserver.txt file.
The best answer to this question: The .(dot) twb is the most common file extension used in Tableau, which presents an XML format file and comprises all the data present in each dashboard and sheet like what fields are used in the views, styles and formatting that are applied to a sheet and dashboard.
But this workbook does not contain any data. The Packaged Workbook merges the data in a Tableau workbook with the local data available (which is not on server). A. (dot) twbx serves as a zip file this includes custom images if any. Packaged Workbook allows users to share their workbook information with other Tableau Desktop users and let them open it in Tableau Reader.
The best answer to this question: A maximum number of 32 tables can be joined in Tableau. A table size must also be limited to 255 columns (fields).
Here were the answers to the most commonly asked Tableau interview questions, for more such interesting data analytics news, job updates and discussions follow our daily uploads from DexLab Analytics. We have recently launched our new branch in Pune, so, now Maharashtrians can also get their data analytics certification from DexLab Analytics, we add values to dull data!
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Are you planning to pursue a Tableau training course in Delhi? Then you must be well aware of this common confusion about the difference between these two widely used maps. There are two very useful charts which help in analyzing data, heat maps and tree maps. Heat maps and tree maps are highly insightful visualizations. However, many a times, there is a confusion between the two due to which analysts either use misuse it or totally avoid using it.
This article will help to draw a clear line between heat maps and tree maps, thus enabling analysts pursuing tableau certification, Gurgaon to create better visualizations.
We the faculty at Dexlab Analytics, the premiere Tableau Training Institute in Gurgaon aim to clarify this common doubt with this brief discussion on these two maps.
Heat map is a type of visualization tool that is very apt to compare different categories. It helps to visualize measures against dimensions with the help of colors and size to compare one or more dimensions & up to two measures. The layout is similar to a text table with variations in values encoded as colors. In heat map, you can quickly see a wide array of information.
In a heat map, one measure can be assigned to the color and another measure can be assigned to the size.
Quick Hands-On: Shows the sales and profit in all regions for different products category and sub-Category.
Analysis of visualization: The profit is represented by the color and ranges from red for loss to green for profit. The total sales are represented by the size.
Hence, it is very easy to understand the performance of different products in different regions, at one glance, just by looking at the heat map.
Tree maps are a relatively new feature in Tableau, first appearing in version 8.0. The ‘tree map’ is a chart type that displays hierarchical or part-to-whole relationships via rectangles. In case of hierarchical (tree-structured) data these rectangles are nested. The space in the view is divided into rectangles that are sized and ordered by a measure. Nested rectangles mean that hierarchy levels in the data are expressed by larger rectangles (above in the hierarchy) containing smaller ones (below in the hierarchy). The rectangles in the tree map range in size from the top left corner of the chart to the bottom right corner, with the largest rectangle positioned in the top left corner and the smallest rectangle in the bottom right corner.
In a tree map 1 or more dimensions & up to 2 measures are used to create such a map.
Quick Hands- On: Show the sales and profit in all regions for different products category and Sub-Category.
Analysis of the visualization: The profit (color) and sales (size) of products are given at a Category and Sub- Category level. Bigger the size of the node, greater is the sales in that state. Similarly, the greener the node, more is the profit in that state.
Summary: A slight disadvantage of using tree maps in Tableau is that, as the number of items increase, the amount of space allocated for each item decreases. Hence, the area available to print the labels, become small. As a result, usually, in a tree map almost all the squares or nodes will appear blank. This defect can be overcome by providing appropriate tooltips for each node. Like in heat maps, measures can be assigned to give different colors and sizes to the nodes in the tree map.
To learn the right use of these two maps in Tableau we recommend seeking a corporate Tableau Training in Delhi NCR for better understanding of this complex statistical application.
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