Is Actually Adobe Analytics Adhoc Evaluation A Business Intelligence Tool – The promise of self-service analytics is that users of all technical skill levels will be able to investigate their data in ways that make sense to them, without the help of IT or data experts. The modern iteration of this principle is workflow-infused analytics, where the right piece of actionable intelligence is presented to the right user at the right time and place, tied to the best action they can take based on that information. It is a fusion of form and function that has the ability to supercharge processes of all kinds and evolve businesses.
According to a recent survey conducted by Harvard Business Review (HBR), 77% of companies said that the intelligence of analyzed data was important to their business success. To facilitate this success, data experts must dig deep into datasets and ask complex questions that will help evolve businesses and unlock new opportunities, often referred to as “ad hoc analysis.” But these game-changing revelations are useless if the people who need the results can’t access or understand them.
Is Actually Adobe Analytics Adhoc Evaluation A Business Intelligence Tool
Here’s how ad hoc analytics plus the right BI and analytics platform square this circle. To understand this relationship, let’s investigate why companies aren’t doing it as much as they could, and how the right BI platform can empower data teams and business users to get more out of data.
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Many companies understand the value that ad hoc analytics can bring to helping a business evolve, but still don’t devote time and resources to it. Often this is just because the data teams are too busy.
Check any job listings site and you’ll see that coders with data skills are in high demand, but graduates with relevant training are in short supply (not to mention experienced data scientists). Departments with high demand for analytics are likely using BI tools or relentlessly trying to implement the right one: Dresner’s 2021 Wisdom of Crowds® Business Intelligence Market Study shows that operations, executive management and finance departments often lead when it’s about to BI implementation.
These are all departments where daily granular intelligence derived from analyzed data is needed, but also where ad hoc analytics can help make strategic decisions and see the big picture. The right self-service, intelligence-infused platform can help protect data specialists from being inundated with an endless flood of basic questions (“What was our total revenue for North America in 2020?”) so they can focus on analytics of greater value. projects
If your company isn’t engaging its data team for this kind of work that drives evolution, chances are you don’t have the right BI platform to empower users of all skill levels. The HBR report showed that 51% of respondents still went outside of their workflows to find analytics, and nearly 20% returned to IT with each new query. Without a solid platform that infuses information into workflows, data teams are stuck running around putting out fires and delivering lower-value reports (a lesser type of ad hoc analysis) to countless users. That’s not what you hired them for!
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The right analytics and BI platform not only enables you to gain more insights from your company’s data warehouses, drive smarter decisions and open up new revenue streams, it transforms every aspect of your business that it affects.
We’ve already established how a robust platform that infuses analytics into workflows frees your data team from doing small, one-off tasks for each team. It also empowers those teams to increasingly answer their own questions without the need for technical skills, even offering the information they need without asking for it, where and when it’s most valuable. The platform also shows teams what they
– With ad hoc analysis. Now, when they ask the data team for something, everyone involved knows it’s of greater value.
A perfect example from Sisense client Skullcandy involves using Python code to perform sentiment analysis on a collection of customer reviews to better understand how customers feel about products. This helped Skullcandy with customer service interactions, warranty budget planning, and ultimately some product design changes. This is the power of ad hoc analytics!
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In addition, a BI platform serves as the missing link between the data team and the users who need the deeper intelligence they have discovered. Once the ad hoc data analysis is complete, the data team can infuse the results back into the workflows of the people who requested them, presenting the information in a way that can be examined, explored and understood by the less technical, without any additional help from experts.
Running a business is a collaborative act. Even in a four-person startup, where everyone does multiple jobs, no one person can do everything or answer every question. The evolution of BI from IT-driven to self-service to analytics-infused has allowed non-technical users to get more and more out of their data without the assistance of the IT/data team, but that only frees up these data experts to do more game-changing things with your team. skills
The right analytics and BI platform helps users of all types go above and beyond for themselves and illuminates where ad hoc analytics can really take business to the next level. The data team jumps into action, performs the analysis, and sends the information back to whoever needs it, in a way that makes sense to them. That’s the new promise of BI: unlocking the power of ad hoc analytics easily.
Scott Castle is the Vice President and General Manager of Cloud Data Teams at Sisense. He brings over 25 years of experience in software development and product management at leading technology companies including Adobe, Electric Cloud and FileNet. Scott is a prolific writer and speaker on all things data, appearing at events such as the Gartner Enterprise Data Conference, Data Champions, and Strata Data NYC.
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Is a program of professionals and business communities of big data analytics to improve recruitment, partnership and community engagement. This post is going to be a departure from the “normal” content of this blog. Its purpose is to answer one of the most frequent questions I get from many people who read my posts. The title may already reveal what that question is: “Frederik, in your opinion, should companies buy Adobe Analytics or Google Analytics?” And I think there is something fundamentally wrong with this question.
I think the above question can only be answered by some absurd level of generalization that doesn’t do justice to both tools. There are some agencies or consultants who end up doing this comparison to appear neutral and independent or drive SEO traffic to their own sites. This bothered me to the point where I started writing this post to have my personal response ready in the future.
Bear with me on this one. In order to make my point, I first need to go over what bothers me so much about the existing comparisons, only to then completely ignore the title and compare what kind of tools we’re really talking about, and what the real question should be. . Buckle up!
Let me start by mentioning my favorite comparison of Google Analytics and Adobe Analytics on the QA2L blog. I really like it because it really goes into great detail about the differences between both tools on various levels. While that comparison seems like the most comprehensive I’ve seen in a while, it misses the most important point: whether and how those tools are comparable in the first place, and if so, should they be compared at all.
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What do I mean by that? It might sound complicated, but to me GA and AA just don’t fall into the same category
. Those two categories are not the same to me, and I’ll explain the difference a bit later. While tools like Google Analytics may be good enough for web reporting, Adobe Analytics is not
Analysis However, this was not always the case, so let’s quickly look at the history of both tools.
To start our little comparison, I want to show you a very old Google Analytics screenshot. In fact, it’s from 2012:
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Sounds pretty familiar, right? It should, because this is what GA 360 looks like today in 2020:
On the other hand, they certainly did a great job keeping the interfaces consistent. Apart from a bit of a design rearrangement, someone who has been working with GA eight years ago would still feel right at home today. This interface and the reports available on it have been influencing the way web reporting was conceived for many years, setting standards and expectations for our entire industry. That hasn’t changed much with GA4 either, where Google is now trying to establish a new set of reports and metrics that website owners should focus on instead of the rather old reports we see above.
Let’s see what the past looks like for Adobe Analytics. Fortunately, I don’t need to google any old screenshots, since the past is around the
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