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Is Business Intelligence the Latest Buzzword for Technology?

Business Intelligence

Technology is often presented raw, especially when businesses are concerned. Be it an isolated polymer or a large setup with high-end gadgets, technology is meaningless unless it is put to test. This is where Business Intelligence comes to the fore. BI is considered as an efficient conglomerate of techniques— aiding in seamless acquisition of raw data and transformation across usable channels. For starters, Business Intelligence is synonymous to Data Surfacing, to the truest of sense.

Dawn of Business Intelligence

To be precise, we can term this approach as BI technology which is capable of handling truckloads of data. There was a time when BI technology was pretty expensive and only blue-chip firms could afford the same. However, the things have changed with a slew of Business Intelligence tools at our disposal. The new breed of Business Intelligence comprises of multidimensional allocation, denormalization, real-time reporting, probabilistic simulation, open item management, version control and many more metrics. These entities have been incorporated over the past decade, owing to the growth of Smart Data which will be covered in a separate post. Business Intelligence harnesses the power of Smart Data in the user specific market— precisely the entrepreneurial charades. Therefore, it won't be surprising if the BI tools can make the business ROI shoot up the zenith.

Aspects of Business Intelligence: Tools and Tips

BI Tools are extremely specific and targeted. Besides delivering key business insights, these tools can help execute technological strategies as well. For a business to be successful, proper set of tools need to be offered. The trick here is to achieve the perfect balance between automated business and imperfect human processing. When it comes to Business Intelligence, companies generally reply upon the following tools for success:

  1. Spreadsheets

  2. Querying Software

  3. Digital Dashboards

  4. Data Warehousing

  5. Data Mining

  6. Local Systems offering Information

  7. OLAP or Online Analytical Processing

  8. Process Visualization

Not necessarily in the same order, these tools can offer a lot of leverage to the modern day technologies. One such example would be Google's new 'Intelligent Search'— targeting the entrepreneurs. The concept of Springboard is certainly a new approach from Google which has been perpetuating machine learning in the best possible manner. This platform makes use of several BI Tools which will be discussed in the next section.

Business Intelligence Tools for a Cohesive Machine Learning Experience

Similar to Google, Apple and other companies have also adopted an approach cohesive to machine learning. However, taking over companies like Turi won't be of much benefit unless the Business Intelligence is sorted out. Here are some of the aspects that need to be checked in before strategizing the complete idea of an AI-powered platform:

  • Smart Data or Contextual Discovery

Every AI based platform needs to get past the older data models and this is where contextual discovery can help. This tool specifically segregates the areas to look into and keeps out the ones to be ignored. In simpler terms, this section focuses completely on the relevance.

  • Advanced Analytics

This tool deals with the most comprehensive issue of businesses i.e. accessibility. For a venture to be successful, it needs to cater to a wider audience. This is where advance analytics can help. Most machine learning software renditions offer visually intriguing data sets followed by dynamic infographics. Advanced tools and analytics are capable of handling and presenting them in a unified manner. The next iteration to this would be Embedded Analytics, deemed as the future of BI technology.

  • In-Memory Business Intelligence

Data isn't only about storing and relieving but needs to be loaded and offloaded on demand. In-memory computing is therefore an important aspect of AI empowered structures as they offer advanced levels of internal architecture albeit a lighter footprint. In-Memory BI is responsible for the likes of Siri and Cortana responding quickly to our queries.

  • Collaborative BI

This section brings forth the social connect and is the reason behind the interactive power of machine learning. Apart from codes, collaborative BI is an integral part of any functional technology— precisely machine learning. This involves the aspect of decision making which can be used by the companies— according to the user demands.

Bottom Line

Business Intelligence should not be confused with data science. While the former targets the core competencies of a business specific technology, the latter can be leveraged only for real-time benefits. In the future, more and more companies need to leverage BI technologies in order to get the most out of their scientific goals. Then again, the process resembles symbiosis and even the BI technologies are benefited by the latest technologies including mobile, ecommerce, IoT and Cloud Computing.

More on these aspects in the next article.