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Natural Language Processing: The Future of Business Analytics

The past decade has ushered in a groundbreaking new era of tools available to assist businesses in furthering their goals. Specifically, the rapid rise of new technologies and interdisciplinary fields like data science is worthy of note. These advances are being applied to everyday business problems in ways that were unimaginable until recently. Such advances are known as business intelligence, a wide-reaching term that refers to technologies and applications that allow business to make better decisions by leveraging the data they produce naturally as a result of their business processes. One emerging field of note is self-service analytics, a form of business intelligence that allows everyday business professionals to leverage the benefits and insights provided through analytics without the need for lengthy training or an in-depth understanding of data science principles. Self-service analytics, like many other types of business intelligence, has the potential to revolutionize the way everyday business professionals and organizations make decisions. Through democratizing a company’s native data sets, businessmen and women are able to make extremely informed decisions at a pace never before seen.

While the practice of utilizing analytics or data science principles is not revolutionary it its own right, as businesses have been applying these concepts in one form or another for many years, the ability to gain relevant insights from business intelligence platforms is sure to mark a revolutionary change in how companies approach data. Big data, or extremely large data sets that can be analyzed to reveal patterns, trends, or associations, provides a unique opportunity for businesses if approached properly. But how can the owner of a small business or lean startup leverage such advances on limited operating budgets? Thankfully, innovative companies have developed solutions that allow small business owners and lean startup CEO’s to tap into the power of analytics through a method known as natural language processing. This method serves as a sort of translator between requests entered by the user into a search bar and the underlying mathematical computations required to sift through an enterprise’s big data.

Companies such as AskNed, Thoughtspot, Microsoft’s Power BI and are innovators in this space, allowing businesses to easily leverage the transformative power of enterprise analytics. But before we delve into the specifics of how the technology within this space works, let’s develop a baseline understanding of how natural language processing can help advance your business’ goals. For example, say a user enters a query such as, “What were our total sales by region last month?” into the search bar. Thanks to the product offerings of the companies referenced above, your search will quickly return a set of accurate and informative charts, graphs, and reports to help better your understanding of just how well your products or services are selling within a particular region. While this may strike users as a common-sense solution when considering services like Google or Bing, the technology behind such rapidly generated and user-friendly results has actually come about thanks to groundbreaking advancements in the field of artificial intelligence.

So what exactly is natural language processing, and how does it work? To answer that question, we could delve into a long, jargon-filled monologue that covers recent advances in artificial intelligence and how they help make this technology possible. As tempting as that sounds, let’s instead use an analogy to compare the functionality of an everyday web search engine such as Google and a self-service analytics software platform. When you go onto Google, you can simply enter any question or term imaginable into the search bar and get a list of millions upon millions of relevant results instantly. Most importantly, these results are presented to users in an easy to read format. Now, let’s think of the offerings of self-service analytics firms such as AskNed as our search engine. If a business operator wanted to get a quick answer to a detailed question such as, “What were our operating costs in the New England region last quarter?” they could enter the query into their search bar and get an informative answer almost instantly. Business intelligence platforms that rely on self-service analytics return answers to such questions in an easy to understand format that can immediately be applied to important business decisions, just as how a simple Google search can quickly lead you to the closest gas station.

For the casual observer, the functionality of offerings by Google’s search engine and these new self-service analytics startups might appear to be the same. This is by design, as delivering data in a user-friendly and informative format is of the utmost importance. However, under the hood, self-service analytics acts more like a “Analytics-to-English” translator than a traditional search engine. The beauty of natural language processing is that it allows users to communicate with their device or software in a way that feels natural for them. If you’ve ever used Siri or Google Assistant to make a phone call or create a reminder on your calendar, you’ve tapped into the power of natural language processing to make your everyday life more convenient. The point of such technologies is to remove common sources of friction within a user’s everyday life, such as making appointments, entering search questions, or checking the weather. While applications like these digital assistants are certainly useful, the power of natural language processing can be leveraged to an even greater extent, especially in areas where business decision making is concerned.

According to Gartner, by 2019 there will be more analytics-based analysis produced by business intelligence platforms such as self-service analytics software providers than by data scientists themselves. This may be a concerning development if you area data scientists, but leads to an exciting outlook for businesses looking to leverage the power of analytics to improve the ways that they conduct everyday business. Rapid advancements in the fields of artificial intelligence and natural language processing is allowing companies offering analytics software as a service (SaaS) to flourish. These trends can be leveraged by the savvy business executive or lean startup manager in a way that helps your decision making become more responsive to the market trends of your product or service. Think of how much more effective your business could become if you were able to apply the millions of data points created by your company in a way that helps inform and refine your processes.

Such conscious decision making could assist with anything from cutting out waste seen throughout the manufacturing process to ensuring that customers are provided an ever-increasing sense of satisfaction when utilizing your products. In addition to this, the application of self-service analytics on an enterprise-wide scale could allow your company to democratize its data in a way that allows all departments and business sectors to flourish. Arguably, the biggest immediate impact that natural language processing analytics provides is the ability to skip what would likely be a costly and time consuming period of employee training. Instead of your employees spending time to learn the ins-and-outs of a complicated database software language, employees could instead immediately apply the power of analytics to their main job functions. Such a roll out of this technology would not only save money on training expenses and help to avoid lost revenue, but would more importantly allow teams throughout the enterprise to make more well informed decisions in a fraction of the time that would be required to wait for analytics reports to be produced by a traditional data scientist.

In today’s globalized, ever competitive business environment, the most important resource that companies must manage is their time. In an economic environment that is experiencing an ever increasing pace, being able to make changes to business processes at a moments notice can be the difference between delivering a product before a competitor or being such in a state of production hell. But what if such rapid decision making could be well informed by the big data being created naturally as a result of your business’ processes? Would access to near-instantaneous analytics-based insights help to better inform your business’ judgements and make you more competitive in the marketplace? It seems apparent that a small investment in a self-service analytics platform could pay numerous dividends for your business. Whether a well established, perennial Fortune 500 company or a lean and scrappy startup just trying to get off the ground, every company can benefit from leveraging the power of analytics. What once cost huge amounts of time, money, and long training hours can now be achieved through user-friendly software thanks to the powers of artificial intelligence and natural language processing. Regardless of your business’ industry or goals, we are confident that it can benefit from democratizing your companies data and applying it throughout your already established processes.

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