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Furthering its push to deliver user-friendly analytics across the enterprise, Salesforce on Thursday unveiled a new series of apps that are each tailored for a specific business context and role.
Earlier this year the company rolled out a collection of mobile updates to its Wave Analytics Cloud offering, and last month it added a new tool focused on big data. Now, the new line of Wave Analytics Apps is intended to extend the Analytics Cloud further with prepackaged templates designed to allow business users in particular job functions to find context-specific meaning in their data.
Salesforce holds a “home court advantage” in this area thanks to the integration it can offer at multiple levels, including data assets, tools such as Chatter and its platform as a whole, said Howard Dresner, chief research officer with Dresner Advisory Services.
The company is making big promises, but it should be able to deliver on them, Dresner added.
“If they deliver everything they’re saying they will — all the integration, real best practices and the ability to deploy quickly — it’s compelling,” he said.
Of course, it is just a first offering, Dresner pointed out. Still, “it draws a line in the sand.”
Two new reports from Dresner Advisory Services assess the features that users are looking for in BI tools and which vendors are delivering.
Most organizations are generally optimistic about their use of BI reporting tools, but they see a number of roadblocks that threaten to slow their progress toward a more data-driven future, according to Dresner Advisory Service’s latest Business Intelligence Market Study.
Respondents to the survey, which queried about 2,000 BI users, reported plans to steadily increase the number of people within their organizations who use BI tools over the next 36 months. Organizations also intend to expand the number of BI tools in operation. Users most commonly implemented BI tools to create dashboards, improve access to data throughout the business and produce advanced data visualizations.
But even as respondents expressed interest in expanding their use of BI, they reported warning signs that could imperil further progress. For example, the number of respondents who described their BI initiatives as “successful” dropped from 41% last year to 35% this year. The number who said their projects were “somewhat unsuccessful” increased from 8% last year to 10% this year.
As more data lives in the cloud, analytics wants to live there, too. IT, however, has other plans.
Business Intelligence (BI) isn’t for everyone. As my friend has suggested, “Some things can’t be simplified for the mass market, e.g., flying a plane or doing analytics.”
But the cloud does promise to make BI a bit easier, at least for enterprise IT, which traditionally has been tasked with setting it up. The problem, as analyst Howard Dresner indicated, is that enterprise IT has resisted cloud BI. And while IT points to security and privacy as the reasons, the real motivation may be far less noble:
A desire to retain control.
While not surprising—everyone likes a little job security—this antipathy to the cloud may end up rendering IT obsolete.
Editor’s note: Location intelligence is a form of business intelligence software where the dominant dimension used for analysis is location or geography. What kinds of businesses currently use location intelligence in their BI initiatives? Will location intelligence have far-reaching impacts on BI software and business in general? We caught up with one of the world’s foremost thought leaders in business intelligence – Howard Dresner, founder and chief research officer at Dresner Advisory Services – to find out the trends in location intelligence. In this interview he discusses some of the findings from his 2015 Location Intelligence Market Study including user sentiment, implementations, future plans and analysis of vendors’ product support.
Lack of trust is one of the greatest, and mostly unspoken, barriers to success in business intelligence programs. Like the proverbial elephant, it has a huge presence, but most people don’t talk about it within their corporate setting and thus don’t correct the situation.
At one of my #BIWisdom tweetchats held each Friday on Twitter, a participant commented that the lack of trust is “like data security – it isn’t a concern until it bites you.” Those so-called “bites” are likely to occur more frequently now in the contexts of trusting the data as well as trusting people. Here’s why:- Analytics architectures are more distributed, which requires trust in the data. And advanced analytics emphasize data/source verification.
- The growth of cloud BI and mobile BI also exacerbate the issue as they enable collaboration, and people need to trust the people with whom they collaborate.