1. Manual data prep is not enough.
Business users are reinventing the way to prepare and assemble data. Demand for self-service data prep is growing – users are becoming smarter and moving more and more data around to feed different analytics and insights. The reality? Analysts are spending their valuable time massaging data. Manual data prep is no longer enough. At some point there has to be a transition for many companies to move to small enterprise approaches, which govern the data, and manage an increased number of sources through automated workflows. For Tableau to grow more deeply into a company’s true infrastructure, a fully managed data pipeline will be needed. We saw this need at #TC15 with the sentiment, “I no longer want to be the data prep guy.”
2. Tableau 9.1 makes a few key commitments for data.
Tableau is simplifying access to readily available data sources, not innovating for data integration per se… that’s okay and most of their users love it. Tableau worked on accessing any web source using its new web data connector, has provided a robust in-place data interpreter for automated data quality, and now has a unified SDK for simple automated workflow. On the Cloud side, Tableau connects to Amazon Aurora, Google Cloud SQL and a host of Microsoft Azure data warehouses and database services. A cool addition is improved processing speed for the connection to SAP HANA and SAP BW. The Tableau Web Connector (WDC) is also great. Check it out: Using Tableau Web Data Connector (WDC).
3. What will happen with Tableau Drive is uncertain.
This is Tableau’s ticket to bigger enterprise deals. The question will be how to design an agile data platform, with all the features that can span large needs for discovery, prototyping, foundation frameworks and scaling-out. The message was straightforward to the loyal business users – “Despite the proclaimed power of self-service, to spread Tableau across the enterprise, you will need IT (a lot) to help you pull it off.” It’s a classic marketing pull through strategy. See www.tableau.com/drive.
4. Tableau Business Users must share their “enlightenment” with the IT staff.
Who was missing from #TC15? Maybe it was the oft-mentioned and maligned, “IT Staff.” So many smart business analysts mentioned they could not wait to get home and enlighten their teams. Their dilemma? How to really turn their daily routines into enterprise deployments, basically what Tableau’s “Drive” promises from their perspective. This is a work in progress for sure because professional IT Directors are really responsible for the data assets of their company. No visualizations, as compelling as they might be, will change that control.
5. Prototyping is key to successful data management.
What Tableau users are getting right is understanding that prototyping their data integration and analytics is a very important task. This tends to be a balance between automated governance and workflow. The positive impact of data prep has been to cheaply do this activity; but it often falls short because it might not include the combination of the how and the who of the data activity.
6. Orchestration of data flow is becoming more important.
Orchestrating disparate data sets enables companies to create their own symphony of business rules and data alignment, allowing business users to compose processes that can now be automated. This limits human intervention, increases data quality and just make the process go faster. As Tableau users wrestle with more data and a greater pull from analytic viz needs, this is how they will have to keep up. It’s not just bringing the message to the IT department; it’s being part of the solution to manage data. CloverETL’s got a cool approach here. See www.cloveretl.com/products/explore/automation-orchestration.
7. Microsoft SSIS and PowerBI are being challenged by Tableau and data prep.
A major trend at #TC15 was that business users had already moved on from the SSIS/PowerBI to Tableau. Clearly apparent was the need to manipulate Excel and flat files meaningfully, all with the embedded Tableau mini-data prep. Now, Microsoft is countering this with their BI-DataPrep-SQL combo. The result will be how Microsoft invests in this space today and into the future. See sqlmag.com/blog/what-coming-sql-server-2016-business-intelligence.
By the way, this issue all goes away with a comprehensive approach to data integration. Be it Informatica (www.informatica.com) or CloverETL (www.cloveretl.com), this is easily managed into a better Tableau experience.
8. AWS is important.
Cloud, right? Of course. Amazon Web Services (AWS) is Tableau’s Partner of the Year and likely their most dear technology partner. No one can ignore an $8B business, doubling year to year. The energy at #TC15 we saw focused on how cloud data could be managed to provide the most insights, and how to manage that from a cost basis point of view. The cost of S3 storage, EC2 compute or RedShift database has to be calculated as data needs really grow.
Tableau business users – say retail or marketing, for example – know AWS is great to get started quickly. But without an architecture strategy on the value of the data as it relates to compelling Tableau visualizations, customers may be locking themselves into wasting money. Cloud can be expensive. Business users often don’t have to make these tough decisions with smaller data sets; but with growth, their best friends in IT aren’t going to be happy with a big bill for a small picture.