Are you in Sales Operations, Marketing Operations, Sales Representative/Manager, or Marketing Professional? It’s no secret that if you are, you benefit greatly from the power of performing your own analysis, at your own rapid pace. When you have a hunch, you can easily test it out by visually analyzing data in Tableau without involving IT. When you are faced with tight timeframes in which to gain business insight from data, being able to do it yourself in the time you have available and without technical roadblocks makes all the difference.
Self-service Business Intelligence is powerful! However, we all know it can be even more powerful. When needing to put together an analysis, we know that you spend about 80% of your time putting together data, and then just 20% of your time analyzing data to test out your hunch or gain your business insight. You don’t need to accept this anymore. We want you to know that there is a better way!
We want to allow you to Flip Your Division of Labor and allow you to spend more than 80% of your time analyzing data to test out your hunch or gain your business insight and less than 20% of your time putting together data for your Tableau analysis! That’s right. You like it. No, you love it. No, you are ready to run laps around your chair in sheer joy!! And you should feel this way. You now can spend more time on the higher value activity of gaining business insight from the data, and even find copious time to spend with your family. How’s that?
Project Springbok is a visionary new product designed by Informatica with the goal of making data access and data quality obstacles a thing of the past. Springbok is meant for the Tableau user, a data person would rather spend their time visually exploring information and finding insight than struggling with complex calculations or waiting for IT. Project Springbok allows you to put together your data, rapidly, for subsequent analysis in Tableau. Project Springbok tells you things about your data that even you may not have known. It does it through Intelligent Suggestions that it presents to the User.
Let’s take a quick tour:
- Project Springbok tells you, that you have a date column and that you likely want to obtain the Year and Quarter for your analysis (Fig 1)., And if you so wish, by a single click, voila, you have your corresponding years and even the quarters. And it all happened in mere seconds. A far cry from the 45 minutes it would have taken a fluent user of Excel to do using VLOOKUPS.
VALUE TO A MARKETING CAMPAIGN PROFESSIONAL: Rapidly validate and accurately complete your segmentation list, before you analyze your segments in Tableau. Base your segments on trusted data that did not take you days to validate and enrich.
- Then Project Springbok will tell you that you have two datasets that could be joined on a common key, email for example, in each dataset, and would you like to move forward and join the datasets (Fig 2)? If you agree with Project Springbok’s suggestion, voila, dataset joined in a mere few seconds. Again, a far cry from the 45 minutes it would have taken a fluent user of Excel to do using VLOOKUPS.
VALUE TO A SALES REPRESENTATIVE OR SALES MANAGER: You can now access your Salesforce.com data (Fig 3) and effortlessly combine it with ERP data to understand your true quota attainment. Never miss quota again due to a revenue split, be it territory or otherwise. Best of all, keep your attainment datatset refreshed and even know exactly what datapoint changed when your true attainment changes.
- Then, if you want, Project Springbok will tell you that you have emails in the dataset, which you may or may not have known, but more importantly it will ask you if you wish to determine which emails can actually be mailed to. If you proceed, not only will Springbok check each email for correct structure (Fig 4), but will very soon determine if the email is indeed active, and one you can expect a response from. How long would that have taken you to do?
VALUE TO A TELESALES REPRESENTATIVE OR MARKETING EMAIL CAMPAIGN SPECIALIST : Ever thought you had a great email list and then found out most emails bounced? Now, confidently determine which emails are truly ones will be able to email to, before you send the message. Email prospects who you know are actually at the company and be confident you have their correct email addresses. You can then easily push the dataset into Tableau to analyze the trends in email list health.
And, in case you were wondering, there is no training or install required for Project Springbok. The 80% of your time you used to spend on data preparation is now shrunk considerably, and this is after using only a few of Springbok’s capabilities. One more thing: You can even directly export from Project Springbok into Tableau via the “Export to Tableau TDE” menu item (Fig 5). Project Springbok creates a Tableau TDE file and you just double click on it to open Tableau to test out your hunch or gain your business insight.
Here are some other things you should know, to convince you that you, too, can only spend no more than 20% of you time on putting together data for your subsequent Tableau analysis:
- Springbok Sign-Up is Free
- Springbok automatically finds problems with your data, and lets you fix them with a single click
- Springbok suggests useful ways for you to combine different datasets, and lets you combine them effortlessly
- Springbok suggests useful summarizations of your data, and lets you follow through on the summarizations with a single click
- Springbok allows you to access data from your cloud or on-premise systems with a few clicks, and the automatically keep it refreshed. It will even tell you what data changed from the last time you saw it
- Springbok allows you to collaborate by sharing your prepared data with others
- Springbok easily exports your prepared data directly into Tableau for immediate analysis. You do not have to tell Tableau how to interpret the prepared data
- Springbok requires no training or installation
Go on. Shift your division of labor in the right direction, fast. Sign-Up for Springbok and stop wasting precious time on data preparation. http://bit.ly/TabBlogs
Are you going to be at Dreamforce this week in San Francisco? Interested in seeing Project Springbok working with Tableau in a live demonstration? Visit the Informatica or Tableau booths and see the power of these two solutions working hand-in-hand.Informatica is Booth #N1216 and Booth #9 in the Analytics Zone. Tableau is located in Booth N2112.
Within every corporation there are lines of businesses, like Finance, Sales, Logistics and Marketing. And within those lines of businesses are business users who are either non-technical or choose to be non-technical.
These business users are increasingly using Next-Generation Business Intelligence Tools like Tableau, Qliktech, MicroStrategy Visual Insight, Spotfire or even Excel. A unique capability of these Next-Generation Business Intelligence Tools is that they allow a non-technical Business User to prepare data, themselves, prior to the ingestion of the prepared data into these tools for subsequent analysis.
Initially, the types of activities involved in preparing this data are quite simple. It involves, perhaps, putting together two excel files via a join on a common field. However, over time, the types of operations a non-technical user wishes to perform on the data become more complex. They wish to do things like join two files of differing grain, or validate/complete addresses, or even enrich company or customer profile data. And when a non-technical user reaches this point they require either coding or advanced tooling, neither of which they have access to. Therefore, at this point, they will pick up the phone, call their brethren in IT and ask nicely for help with combining, enhancing quality and enriching the data. Often times they require the resulting dataset back in a tight timeframe, perhaps a couple of hours. IT, will initially be very happy to oblige. They will get the dataset back to the business user in the timeframe requested and at the quality levels expected. No issues.
However, as the number of non-technical Business Users using Next-Generation Business Intelligence tools increase, the number of requests to IT for datasets also increase. And so, while initially IT was able to meet the “quick hit dataset” requests from the Business, over time, and to the best of their abilities, IT increasingly becomes unable to do so.
The reality is that over time, the business will see a gradual decrease in the quality of the datasets returned, as well as an increase the timeframe required for IT to provide the data. And at some point the business will reach a decision point. This is where they determine that for them to meet their business commitments, they will have to find other means by which to put together their “quick hit datasets.” It is precisely at this point that the business may do things like hire an IT contractor to sit next to them to do nothing but put together these “quick hit” datasets. It is also when IT begins to feel marginalized and will likely begin to see a drop in funding.
This dynamic is one that has been around for decades and has continued to worsen due to the increase in the pace of data driven business decision making. I feel that we at Informatica have a truly unique opportunity to innovate a technology solution that focuses on two related constituents, specifically, the Non-Technical Business User and the IT Data Provisioner.
The specific point of value that this technology will provide to the Non-Technical Business User will enable them to rapidly put together datasets for subsequent analysis in their Next-Generation BI tool of choice. Without this tool they might spend a week or two putting together a dataset or wait for someone else to put it together. I feel we can improve this division-of-labor and allow business users to spend 1-2 weeks performing meaningful analysis before spending 15 minutes putting the data set together themselves. Doing so, we allow non-technical business users to dramatically decrease their decision making time.
The specific point of value that this technology will provide the IT data provisioner is that they will now be able to effectively scale data provisioning as the number of requests for “quick hit datasets” rapidly increase. Most importantly, they will be able to scale, proactively.
Because of this, the Business and IT relationship has become a match made in heaven.