By 2018, it was estimated that more than half of large organizations competed using advanced analytics and proprietary algorithms. Despite this, data analytics is sometimes seen by businesses as being too complicated. Simply put, many businesses see advanced analytics and data science as being too costly, time-consuming, and inaccurate to justify more than a token effort at implementation.

However, with more and more data being generated every day, roughly 2.5 quintillion bytes of data daily, many organizations are discovering that they can gain a real advantage over their competition simply by mining any and all available information and using advanced analytics for useful insights. As such, companies that continue to shun business analytics as unnecessary may find themselves falling further and further behind their more data-driven competitors, who are flexing their advanced analytics muscles.

The truth is that data analytics, particularly in regard to how data stores are being managed, can play a significant role in an organization’s success.

Data analytics is designed for businesses that want to make good use of the data that they are taking in. Businesses that can use data analytics properly are more likely than others to succeed and thrive. With all of the advantages of data analytics, the key benefits can be described in this way:

  • Data analytics reduces the costs associated with running a business. This is due to the business’ increased understanding of particular trends uncovered in the data being reviewed.
  • Data analytics cuts down the time needed to come to strategy-defining decisions. As conclusions are mined from the available data, they are presented in a clear and accessible way, allowing business leaders to quickly move forward.
  • Data analytics helps to more accurately define customer trends. This information can be used in the creation of new products or services, allowing for better fulfillment of customer needs.

But despite the benefits of data analytics, it’s becoming clear that forward-thinking organizations should move beyond traditional analytics, and into advanced analytics.

While it can be difficult to pin down an exact definition of advanced analytics, the idea is that it’s a more complicated, more effective form of data analysis. Advanced analytics entails a deeper review of data in many forms.

More specifically, there are a number of factors inherent in the concept of advanced analytics:

  • Data and text mining may be used to find specific trends or pieces of data.

  • Visualization is used to gather existing information for the creation of visual images showing trends, comparisons, and other statistical points.

  • Cluster analysis helps to take pieces of data that are similar to each other and separate that data from other groups. This is to facilitate effective comparisons.

  • Simulations may be generated to figure out what future trends or results might occur based on the statistics being reviewed.

  • Predictive analytics uses techniques associated with data mining, machine learning, statistical analysis, and others to generate highly accurate predictions about future business trends.

Advanced analytics specifically focuses more on forecasting, using the data it gathers to find trends that can be used to determine what might happen in the future. For example, a what-if analysis can be generated by an advanced analytics program. A what-if analysis can be run using different values, allowing for the consideration of hypothetical data or circumstances. This type of analysis helps to see what might happen over time, thus making it easier for a business to prepare for any uncertainty that might pop up.

Given the growing familiarity and popularity of data analytics, there are a number of advanced analytics programs available on the market. However, while each program offers big data solutions, not all are created equal. But while the programs themselves may offer different foci and capabilities, generally speaking, the tasks they are expected to perform will be similar from one company to the next. As such, there are certain characteristics to look for in any analytics solution that will help you gauge just how effective it will be in improving your business.

Perhaps the most important factor in determining how effective an analytics tool will be is usability. The tool itself will more than likely be used by a wide range of individuals, departments, and systems within an organization. It will need to be designed for compatibility with a large number of platforms and other tools. Choosing a program that can function optimally across a variety of platforms can help promote collaboration between users. Often, in order for this to be possible, the program itself will need to be cloud-based.

Likewise, the interface itself will need to be intuitive enough for non-IT users to quickly master it. Data visualization makes it possible for large amounts of information to be shared visually, allowing users to quickly grasp important information, and built-in tutorial programs (as well as other help features such as live chat and telephone support) can help even the least tech-savvy of users learn to operate the system.

And even though the basic function of an analytics tool is going to remain very similar across industries, the organizations that employ those tools are often as different as night and day. No one business is exactly like any other, which means that no single, out-of-the-box analytics solution is likely to be a perfect fit for any particular organization. Advanced analytics software that can be adapted to fit existing systems and processes allows for easier integration and higher adoption rates.

As for the data itself, advanced data analytics programs that process data in real time (rather than as batches) provide users with the advantage of always being able to work with data that is completely current.

Advanced analytics solutions that include these specific features are much more likely to improve business functions and result in a higher ROI than more limited analytics options. That being said, few analytics tools offer the full range of functionality at a cost that is scalable but do not let that discourage you from finding the best fit for your company.

Operating entirely from the cloud with no extra software required, Salesforce’s advanced analytics tools can help businesses get the most out of their data. Augmented analytics are the future, and the Salesforce Platform is helping businesses in that realm. Einstein Analytics works by offering data-driven analysis on any device, allowing organizations to take action immediately. Additionally, users can customize different data stores as necessary to fit their organization’s unique needs. Salesforce advanced analytics tools are designed mobile-first, meaning that the entire tool set is fully compatible on any platform or device in real time. Let Salesforce help you with your analytics business, for it’s a part of your business that’s complex. Having an experienced advanced analytics partner on your side is critical if you hope to compete with your competition.
While there may have been a time when data analytics was of minimal importance to businesses, that time has passed. By 2020, predictive and prescriptive analytics will attract 40% of enterprises’ net new investment in business intelligence and analytics. Augmented analytics may also be a new area of focus. Advanced analytics provides the boost that every organization needs to be able to secure its own future, and that is a complication that any business leader would be happy to address.
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