BUSINESS ANALYTICS TOOLS

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By Nandha Infotech Students

Business analytics tools are types of application software which retrieve data from one or more business systems and combine it in a repository, such as a data warehouse, to be reviewed and analysed.

  • SAP Business Intelligence. SAP Business Intelligence offers several advanced analytics solutions including real-time BI predictive analytics, machine learning, and planning & analysis. …
  • MicroStrategy. …
  • Sisense. …
  • SAS Business Intelligence. …
  • Yellowfin BI. …
  • QlikSense. …
  • Zoho Analytics. …
  • Systum.

1. SAP Business Intelligence

SAP Business Intelligence offers several advanced analytics solutions including real-time BI predictive analytics, machine learning, and planning & analysis. The Business Intelligence platform in particular, offers reporting & analysis, data visualisation & analytics applications, office integration and mobile analytics. SAP is a robust software intended for all roles (IT, end uses and management) and offers tons of functionalities in one platform.

2. MicroStrategy[s1]

MicroStrategy is a business intelligence tool that offers powerful (and high speed) dashboarding and data analytics which help monitor trend, recognise new opportunities, improve productivity and more. Users can connect to one or various sources, whether the incoming data is from a spreadsheet, cloud-based or enterprise data software. It can be accessed from your desktop or via mobile.

3. Sisense

Then the Sisense business intelligence tool might be for you. This user-friendly tool allows anyone within your organisation to manage large and complex datasets as well as analyse and visualise this data without your IT department getting involved. It lets you bring together data from a wide variety of sources as well including Adwords, Google Analytics and Salesforce. Not to mention, because it uses in-chip technology, data is processed quite quickly compared to other tools.

4. SAS Business Intelligence

While SAS’ most popular offering is its advanced predictive analytics, it also provides a great business intelligence platform. It is self-service tool that allows to leverage data and metrics to make informed decisions about their business. Using their set of APIs, you are provided with lots of customisation options, and SAS ensures high-level data integration and advanced analytics & reporting.

5. Yellowfin BI

Yellowfin BI is a business intelligence tool and ‘end-to-end’ analytics platform that combines visualisation, machine learning, and collaboration. You can also easily filter through tons of data with intuitive filtering (e.g. checkboxes and radio buttons) as well open up dashboards just about anywhere (thanks to this tool’s flexibility in accessibility (mobile, webpage, etc.).

6. QlikSense

QlikSense is a product of Qlik, a company also known for another business intelligence tool called QlikView. You can use QlikSense from any device at any time. The user interface of QlikSense is optimized for touchscreen, which makes it a very popular bi tool. A big difference with QlikView is the feature Storytelling. Users add their experience to the data and by using snapshots and highlights making the right analysis and decisions has become a lot easier

7. Zoho Analytics

Use Zoho Analytics for in depth reporting and data analysis. This business intelligence tool has automatic data sync and can be scheduled periodically. You can easily build a connector by using the integration API’s. Blend and merge data from different sources and create meaningful reports. With an easy editor you create personalized reports and dashboards enabling you to zoom into the important details.

8. Systum

Systum is a Business Intelligence tool that helps organisations streamline and consolidate processes across multiple B2B and B2C channels so that they can boost productivity as well as efficiency. It includes a number of sales features, built-in CRM, Inventory Management, a B2B portal and more. Systum also offers a wide range of integration options with – among others – Amazon, eBay, and Quickbooks.

9. Microsoft Power BI



Microsoft Power BI is a web-based business analytics tool suite which excels in data visualisation. It allows users to identify trends in real-time and has brand new connectors that allow you to up your game in campaigns. Because it’s web-based, Microsoft Power BI can be accessed from pretty much anywhere. This software also allows users to integrate their apps and deliver reports and real-time dashboards.
 

10. Looker



Data discovery app, Looker is another BI tool to look out for! This platform integrates with any SQL database or warehouse and is great for startups, midsize-businesses or enterprise-grade businesses. Some benefits of this particular tool include ease-of-use, handy visualisations, powerful collaboration features (data and reports can be shared via email or USL as well as integrated with other applications), and reliable support (tech team).

11. Clear Analytics

Where are all my Excel fans out there? This BI tool is an intuitive Excel-based software that can be used by employees with even the most basic knowledge of Excel. What you get is a self-service Business Intelligence system that offers several BI features such as creating, automating, analysing and visualisation your company’s data.

12. Tableau



Tableau is a Business Intelligence software for data discovery and data visualisation. With the software you can easily analyse, visualise and share data, without IT having to intervene. Tableau supports multiple data sources such as MS Excel, Oracle, MS SQL, Google Analytics and SalesForce. Tableau is free for personal use. However, if you want more, the price can go up quickly. But of course, this will give you something in return: well-designed dashboards that are very easy to use. Additionally Tableau also offers three standalone products: Tableau Desktop (for anyone) and Tableau Server (analytics for organisations), which can be run locally and Tableau Online (hosted analytics for organisations).


13. Oracle BI



Oracle BI is an enterprise portfolio of technology and applications for business intelligence. This technology gives users pretty much all BI capabilities, such as dashboards, proactive intelligence, alerts, ad hoc, and more. Oracle is also great for companies who need to analyse large data volumes (from Oracle and non-Oracle sources) as it is a very robust solution.


14. Domo



 Domo is a completely cloud-based business intelligence platform that integrates multiple data sources, including spreadsheets, databases and social media. Domo is used by both small companies and large multinationals. The platform offers micro and macro level visibility and analyses. From cash balances and listings of your best selling products by region of the marketing return on investment (ROI) for each channel. The only let down about Domo is that it is difficult to download analyses from the cloud to calculations


15. IBM Cognos Analytics



Cognos Analytics is an AI-fueled business intelligence platform that supports the entire analytics cycle. From discovery to operationalization.You can visualize, analyze and share actionable insights about your data with your colleagues. A great benefit of AI is that you are able to discover hidden patterns, because the data is being interpreted and presented to you in a visualized report.

DATA ANALYTICS TOOLS

To conclude, we can say that Tableau Public is easy to use and provides many data analysis solutions with different features. RapidMiner is a great data analysis software for machine learning, is easy to use and provides a powerful GUI. KNIME is a free and open source analytics platform which is easy to learn

  • R Programming. R is the leading analytics tool in the industry and widely used for statistics and data modeling. …
  • Tableau Public: …
  • SAS: …
  • Apache Spark. …
  • Excel. …
  • RapidMiner:
  • KNIME. …
  • Qlik View 

 R Programming

R is the leading analytics tool in the industry and widely used for statistics and data modeling. It can easily manipulate your data and present in different ways. It has exceeded SAS in many ways like capacity of data, performance and outcome. R compiles and runs on a wide variety of platforms viz -UNIX, Windows and MacOS. It has 11,556 packages and allows you to browse the packages by categories. R also provides tools to automatically install all packages as per user requirement, which can also be well assembled with Big data.

2. Tableau Public:

Tableau Public is a free software that connects any data source be it corporate Data Warehouse, Microsoft Excel or web-based data, and creates data visualizations, maps, dashboards etc. with real-time updates presenting on web. They can also be shared through social media or with the client. It allows the access to download the file in different formats. If you want to see the power of tableau, then we must have very good data source. Tableau’s Big Data capabilities makes them important and one can analyze and visualize data better than any other data visualization software in the market.

3.Python

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Python is an object-oriented scripting language which is easy to read, write, maintain and is a free open source tool. It was developed by Guido van Rossum in late 1980’s which supports both functional and structured programming methods.
Phython is easy to learn as it is very similar to JavaScript, Ruby, and PHP. Also, Python has very good machine learning libraries viz. Scikitlearn, Theano, Tensorflow and Keras. Another important feature of Python is that it can be assembled on any platform like SQL server, a MongoDB database or JSON. Python can also handle text data very well.

4. SAS:

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Sas is a programming environment and language for data manipulation and a leader in analytics, developed by the SAS Institute in 1966 and further developed in 1980’s and 1990’s. SAS is easily accessible, managable and can analyze data from any sources. SAS introduced a large set of products in 2011 for customer intelligence and numerous SAS modules for web, social media and marketing analytics that is widely used for profiling customers and prospects. It can also predict their behaviors, manage, and optimize communications.

5. Apache Spark

The University of California, Berkeley’s AMP Lab, developed Apache in 2009. Apache Spark is a fast large-scale data processing engine and executes applications in Hadoop clusters 100 times faster in memory and 10 times faster on disk. Spark is built on data science and its concept makes data science effortless. Spark is also popular for data pipelines and machine learning models development.
Spark also includes a library – MLlib, that provides a progressive set of machine algorithms for repetitive data science techniques like Classification, Regression, Collaborative Filtering, Clustering, etc.

6. Excel

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Excel is a basic, popular and widely used analytical tool almost in all industries. Whether you are an expert in Sas, R or Tableau, you will still need to use Excel. Excel becomes important when there is a requirement of analytics on the client’s internal data. It analyzes the complex task that summarizes the data with a preview of pivot tables that helps in filtering the data as per client requirement. Excel has the advance business analytics option which helps in modelling capabilities which have prebuilt options like automatic relationship detection, a creation of DAX measures and time grouping.

7. RapidMiner:


RapidMiner is a powerful integrated data science platform developed by the same company that performs predictive analysis and other advanced analytics like data mining, text analytics, machine learning and visual analytics without any programming. RapidMiner can incorporate with any data source types, including Access, Excel, Microsoft SQL, Tera data, Oracle, Sybase, IBM DB2, Ingres, MySQL, IBM SPSS, Dbase etc. The tool is very powerful that can generate analytics based on real-life data transformation settings, i.e. you can control the formats and data sets for predictive analysis.

8. KNIME

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KNIME Developed in January 2004 by a team of software engineers at University of Konstanz. KNIME is leading open source, reporting, and integrated analytics tools that allow you to analyze and model the data through visual programming, it integrates various components for data mining and machine learning via its modular data-pipelining concept.

9. QlikView

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QlikView has many unique features like patented technology and has in-memory data processing, which executes the result very fast to the end users and stores the data in the report itself. Data association in QlikView is automatically maintained and can be compressed to almost 10% from its original size. Data relationship is visualized using colors – a specific color is given to related data and another color for non-related data.

10. Splunk:

Splunk is a tool that analyzes and search the machine-generated data. Splunk pulls all text-based log data and provides a simple way to search through it, a user can pull in all kind of data, and perform all sort of interesting statistical analysis on it, and present it in different formats.

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