Embeded Analytics Vs Business Intelligence

    In this article, will understand these terms better and illustrate the differences prominently.

    
    Embedded analytics and business intelligence are the two buzzwords in the era of modern business. A few decades ago, business analysis was done on Microsoft Excel, but after big data made an entrance into the market, it has not only changed the shape of technology but also changed a lot in the field of business analysis.

The Concept

   Business Intelligence is a technology-driven process that encompasses technologies, systems, people, tools, methodologies, etc. allowing an organisation to collect data from both internal and external systems for analysing, developing and running queries in the variety of structured and unstructured data that helps in guiding operational decisions in a business.
     For example, Starbucks uses the collected data of individualised purchase by their customers. They then use BI software to predict what purchase and offers an individual customer is likely to be interested in. Another instance is Oracle, where the entire user experience has been streamlined, demonstrating their continued commitment to making analytics as fast, flexible, and friendly as they are powerful and robust.

Oracle Advanced Analytics

        Here we have a new features and functionalities is now available for Oracle Database, that enhances the database into a platform for business analytics. Oracle Advanced Analytics, a combination of Oracle Data Mining and Oracle R Enterprise, delivers predictive analytics, data mining, text mining, statistical analysis, advanced numerical computations and interactive graphics inside the database.

R Programming:

        R program is an open statistical computing and graphics language. Its started in 1993 developed by “Ross Ihaka” and “Robert Gentleman” as an alternative to SAS, SPSS and other proprietary statistical Packages, Originally, they called as “S”, and renamed to “R” in 1996. R possesses an extensive catalogue of statistical and graphical methods. It includes machine learning algorithm, linear regression, time series, statistical inference to name a few. Most of the R libraries are written in R, but for heavy computational task, C, C++ and Fortran codes are preferred. It is mainly used by statisticians and data miners to develop statistical software for analysis of Data.

Parameters on NQSConfig.INI: Configuration Settings

              The Oracle BI Server software uses an initialization file called NQSConfig.INI to set parameters upon startup. Each instance of the Oracle BI Server has its own NQSConfig.INI file. This initialization file includes parameters to customize behavior based on the requirements of each individual installation. When you update NQSConfig.INI parameters for a clustered deployment, ensure that you make the change in the NQSConfig.INI file for each instance of the Oracle BI Server. 

About Parameters in the NQSConfig.INI File

          This appendix lists the NQSConfig.INI file parameters and gives a brief description and any required syntax for each parameter. The parameters are generally listed in the order they appear in the configuration file.

Note: 

If you attempt to manually update NQSConfig.INI parameters that are centrally managed by Fusion Middleware Control, then the manually updated values are ignored, because the value set in Fusion Middleware Control overrides the value in the file. If you must manually update these settings, then you must disable all configuration through Fusion Middleware Control (not recommended).

Looker & LookML functioning in OBIEE

Looker & Features..           

Looker has a web-based interface that can be used to exploit the expertise of companies’ analytics teams. Using the system, teams can build and share reports in an instant helping their organization use data to boost business decisions and actions. The software is run in database, allowing limitless drill paths and queries. Looker does not depend of cubing of data, intermediary storage or ETL, making it easier to view and compile the data.       

Looker also lets users build their own analytic modules and design visualizations using a single code. Queries can be easily produced and optimized with the platform’s ML code. It can analyse both web-hosted and SQL data and is able to accommodate well over 25 data variations. This piece of software has been helping companies boost customer satisfaction and convert site traffic into eCommerce data.

Looker is best-known for developing an easier approach to data analytics, namely a brand-new database query language call LookML. The language operates like a simplified version of SQL which is reusable and modular, and thus, way easier to learn for first-time users.