All software providers will tell you that their platforms can finally put an end to data silos -- but when it comes...
to data integration challenges, companies should exercise some healthy skepticism. Salesforce is an exception.
Salesforce clouds promise to bring lots of data together to provide a 360-degree view of customers, accounts and more into a single interface on a single platform, yet 76% of the more than 1,500 companies that took part in Blue Wolf Group LLC's 2015 "The State of Salesforce" report struggle with data integration challenges. Salesforce Wave -- or Salesforce Analytics Cloud -- may be able to change that.
Any organization that wants to remain competitive needs to be serious about analytics, and in fact, most are -- 68% of companies responding to "The State of Salesforce" plan to invest in analytics in the coming year. Their end goal? To help their business make data-driven decisions to achieve results. Analytics are crucial. Without data or insight, you're forced to rely on intuition and gut instincts.
Unfortunately, organizations large and small are plagued by these. We often hear, "I don't want to look at my data. It's a mess. I don't know where to start." Organizing and managing data so that you can derive insights can seem so daunting that many companies just ignore it. But you can't make business decisions based on a hunch -- your results will suffer. If you're struggling with unclean or siloed data, you must understand the root of the problem. Here, we'll cover the two biggest challenges companies face when integrating data from multiple clouds, or third-party data into your current Salesforce instance -- and what you can do to fix them now.
Challenge No. 1: Seeing your data
Getting access to data is only as valuable as being able to understand the context in which you want to use it. Think about it this way: You have tons of data, but are you really seeing insights that matter to your employees and your organization?
Imagine you're the head of customer service at your organization, and you want to understand the health of your customer today. You're interested in honing in on a specific set of data: revenue trends over time, the last dozen surveys completed, the top five product SKUs purchased during the past six months and only poor customer call center cases. With traditional business intelligence (BI) tools, it would be almost impossible to see this level of diverse and customized data, regardless of granularity, at the same time. You would need to run four separate reports, compare numbers and likely spend your entire day looking for an answer. This is why we see companies relying on intuition, not data, when drawing conclusions about their business -- it's just too complicated and time consuming to get the insights they want when they need them.
Tools like Salesforce Wave are huge differentiators here. With Wave, you can display any data at the same time on the same dashboard, regardless of its complexity of source or granularity. You no longer have to look at mass quantities of data to find that one insight you're seeking.
Challenge No.2: Structure data, then visualize
Traditional BI forces organizations to structure data in a certain way before they can optimize or visualize it. But this can be a huge task for some organizations that don't have the time or resources to manage and organize their data. Furthermore, once the data has been structured with complex schemas or preaggregations, changes in business requirements might cost you months of time to correct. Those experienced with moving data into an analytics tool are familiar with the barriers to the process, such as the need to denormalize data and transform standardized definitions.
With Wave, the barrier is much lower, since you don't need to structure data in a traditional schema. Wave can ingest all data from diverse data sets and effectively create the benefits of denormalized data on the fly. That said, bringing data into Salesforce Wave still takes some manipulation, particularly concerning extract, transform, and load (ETL) tasks, which is why Wave partners with cloud ETL tools like Informatica. While you don't typically have to do as much ETL work with Wave, some companies will probably need to do some data cleanup before moving information into Wave.
In my experience at Bluewolf, I've found this particularly important when it comes time to roll up or preaggregate data before a merge. With traditional BI tools, data is rolled up in a warehouse and pushed out to teams, but teams can't delve deeper to see specific opportunities or cases. For BI tools to handle mass volumes of data, that data needs be preaggregated. But by doing so, you lose the ability to drill down into your data -- and if you need to ever restructure your data after preaggregating, you're in for a long, painful process.
With Wave, companies have three significant benefits. First, teams can work at various degrees of hierarchy and aren't locked into rolled-up views. Second, you can drill down as far as you want into your data, since you don't have to preaggregate it. Third, since you didn't preaggregate your data, changing its structure is simple and fast.
Everyone preaches the gospel of clean data as the ultimate goal -- and while certainly commendable, it's lofty and requires a huge investment of time and resources with diminishing value of returns in some cases. The reality is that you and your company are running your business today. Whatever the data integration challenges you're faced with, that's what you have to work with. Rely on a tool like Wave to expose your best data, and use it to take action today.
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