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Best Data Analytics Tools For Big Data Management, Visualization & Reporting

Posted by Yashpal Shah on Feb, 16, 2021 02:02

The term ‘ Data Analytics’ is the process of analyzing various sets of raw data with the purpose of deriving meaning from them. This process involves the use of several kinds of systems and software. In simple terms, this can be explained as a scientific process of analysing raw data in order to extract meaningful information from it.

The data analytics tools aim at utilizing some techniques to recognize certain patterns and trends in business-related information. Organizations later use this information for the purpose of improving their function patterns and predictive analysis for decision making. Although you can consider data analytic uses for finding bottlenecks, in reality, it can do much more than that

The concept of ‘Business Intelligence’ on the other hand, implies a collection of certain processes for the different business models used to convert the raw data into understandable information. Additionally, organization can later use this converted information for the purpose of business development, expansion, and generating predictive analytics models.

This is a business tool that supports business operations by providing the resources for proper decision-making. Moreover, these tools arrange meaningful information into reports, charts, or graphs depending on the nature of the business of an organization.

What are Data Analytics Tools: An Overview and their functions

The tools used for completing the process of data analysis are termed as ‘Analytics Tools’. These tools can perform the function of data analysis of the raw data in two processes and understood easily by non-technical users. The process to be chosen depends on the kind of data – qualitative or quantitative

Consequently, in a broad sense, analytics tools perform the function of data analytics. This present that data in interactive reports with an intuitive user interface. But, in reality, these tools perform several other functions within the process of data analytics like e.g real-time insight of big data. We can further categorize this as:

Uses of Data Analytics Tools:

uses of data analytical tools
  1.  Chalking out the needs and goals: In the process of data analytics, a company can bring together its investors and chief investors together in order to decide the primary needs and goals of the organization. In this context, the analytic tools act as collaborative tools.
  2. Aiding in collecting data – Analytics tools not only help in deriving meaningful data from raw data sets, but they also help in saving and loading that information into the data warehouse. You can later use this information to create interactive dashboards.
  3. Deleting needless data – Data transformation tools help in processing the meaningful portion of the raw data and deleting the rest.
  4. Statistical Analysis – One of the most important kinds of analysis is statistical analysis. Besides, these analytic tools help to establish statistical models of analyzing information.
  5. Create visual data – Furthermore, these tools act as data visualization tools and come with natural language processing interfaces. Organizations use this to create a graphic user interface. You can store this information for utilizing later for creating interactive dashboards, reports, and other

Advantages of the use of Data Analytics tools in business :

There are manifold advantages of using analytics tools. They can be classified as follows :

  1. Anticipating the future needs – In the modern competitive market, organizations are under increasing pressure to not only retain customers but also understand their individual needs. You can analyze both traditional and digital data in order to understand the customers well. The relevant tools for this purpose provide management solutions, by creating an intuitive interface.
  2. Decreasing the chances of risks – There are various kinds of analytics tools. The Security and Financial tools can aid in the prevention and misuse of both internally and externally relevant data. These predictive models of data analytics along with complete organizational security helps predicting and preventing possible fraudulent activities.
  3. Helping in the creation of products – Products are the life-source of an organization. Effective business analytics solutions can successfully collect data from external sources where the customers express their opinions on certain products. This in turn can help organizations to improve their product quality or manufacturing efficiency.
  4. Personalization of Service: The major companies of the world are currently suffering from the problem of structured data. On the other hand, in a digitally equipped world, customers require hands-on feedback and response from the companies in order to feel valued. This is only possible through the implementation of an advanced data analysis system.
  5. Bringing about improvement in the customer experience – Machine learning models of data analysis are the new trend in the contemporary business arena. Organizations are currently using these models to improve the productive capacity and efficiency of organizations.

Importance of Data Analytics Platforms in increasing business revenue :

Data Analytics has a considerable number of functions and benefits. So, organizations can benefit a great deal from the use of these data analytics tools. Thus, the advantages of using these platforms can be enumerated in the following manner –

  1. Alignment of data according to company goals: The establishment of advanced data analytics methods aid the organization to collect, load and align the meaningful information in the way which suits the company best.
  2. Enforcing developed patterns of service: The format of time series analysis is a kind of data analytics process. It provides the companies necessary information to improve customer services from time to time.
  3.  Improvised Management: Data Analytics platforms as a part of business intelligence tools provide the user organizations with the necessary support in order to improve the internal management process.
  4.  Influential Advertising: The machine learning pattern of data analytical platforms helps chalk out effective methods of advertising to increase the sales of products.
  5. Improved management of products: The predictive model deployment in data analysis helps to proper management of products in an organization. You can achieve this by understanding the individual needs and preferences of the customers to serve them well.

Points to be noted while choosing tools for Data Analysis :

In this digitally driven world, data is the core of all business activities and data-driven decisions have become a vital part of decision making. The smart and concise utilization of this data is integral for the development and enhancement of business activities. 

Data Analytics is an artificial intelligence-driven process by which the companies in the modern business arena try to use the derived meaningful information to their advantage. 

To choose the best analytical tools for a certain organization the following  must be kept in mind :

  1. Proper research – In the beginning, the professionals of an organization must access the current analytical capacities of their software systems for different analytical processes. Various parts of an organization affected by the process of data analytics, for instance, the IT professionals, shareholders, and others for generating actionable insights. This is because a certain process of data analysis influences the sales and revenue patterns of an organization. Thus, the company must consult all these departments in order to discover the current pattern and capability of data analytics present.
  2. Researching the trending analytical tools – The next involves the process of researching the current trending analytical tools and segregation them into several classifications. This will further help in understanding the benefits and drawbacks of the various tools.
  3. Creating a comparison of trends – In the third step, the company must prepare a detailed comparison using interactive visualizations or visual programming between the current data analytics pattern used by the company and the data analytics tool majorly used by most of the organizations in the market.
  4. Creating a decision matrix – The company now must close in on its decision by making a decision matrix. This matrix is a basic scorecard for all the top analytics tools in the market.
  5. Decision Tool – Finally, the tool which supports all the needs of the company or the organization is chosen.  

Microsoft Power BI as a Data Analysis tool :

Benefits of Power BI

You can consider Power BI as a treasure-hub of analytical tools that data analyst uses worldwide by several small and big businesses. Businesses use this to derive meaningful information, act as a data governance solution and share insights with others in the same organization or elsewhere.

 The data analytics with these tools of this service help organizations to create interactive reports, visuals, and dashboards, and everything is done through using cloud storage. The natural language processing format of the Microsoft tools enables the user to type questions in their natural language. Again, the files that are too large to tackle in Excel can be handled here.

In simpler terms, Power BI has the capacity to transform the relevant data of the company into rich visuals that can help in focussing on the important aspects of the data.

EPCGroup with its expertise in Microsoft Power BI consultation has helped numerous organizations to streamline their big data with Power BI reports and custom-built visualizations.

Microsoft Gold Partner USA

Statistical Analysis Tools: With respect to Microsoft BI and Excel

You can use these ‘Statistical Analysis tools’ for statistically analyzing and computing data. ‘There are various data analytics tools that can statistically analyze data. Some of these kinds of analyses range from relatively simple to more complex ones. You can do these simple kinds of analysis with simpler software. But the complex ones need to use more advanced features.

In terms of Microsoft BI, the statistical tools that further the process of data analysis in the system are known as ‘Clustering’, ‘Grouping’, and ‘Binning’.

Is excel a data analysis tool?

The tool used for statistical analysis in Excel is termed ANOVA. It stands for Analysis Of Variance.

Predictive Analysis Tools: An introduction from the viewpoint of Microsoft BI

The concept of Data Analysis can be of three kinds. Among them, predictive analytics is the process of analysing data about past historical events and attempting to derive information. You can later use this information to predict probable future events. You can do this by recognizing a pattern found in the historical or traditional data. 

The predictive analytic model of Power BI is known as power BI AutoML. The reason behind developing this software was to enable people without computer science backgrounds to create high-end, visual models. Consequently, you can achieve this through the establishment of the machine learning model in the system. The predictive insights provide businesses to prepare for situations such as facing risks or others. 

Microsoft Power BI capabilities for real-time data analysis :

The concept of Real-time Analytics is useful in situations where reports and dashboards built with the goal of replying or reporting back quickly to them. This is done to make sure that each report or dashboard created is always up to date with the latest available data. 

The real-time data analytics feature is highly recommended for organizations looking towards enhancing their business in this competitive market. Some organizations like TransAlta, Piraeus, Bank S.A, Intelliscape i.o. 

Microsoft Power BI & Other Data Analysis Tools in 2021 :

Some of the Competitive data analytics tools for Microsoft Power BI  of 2021 are as follows :

What are top Data Analytics Tool:

Tableau

Tableau Software is an American-based company dealing with business intelligence (BI) software systems. It has its headquarters in Seattle, Washington, and was founded in 2003, in Mountain View, California. Additionally, while the Power BI and Tableau have somewhat similar features, they differ majorly on the ground of cost. While Microsoft BI  is more cost-effective, the Tableau subscription is more expensive.  

Qlik Sense

The Qlik is an end-to-end platform that provides services relating to data integration, business intelligence, and data analytics. It was founded in Lund, Sweden, in 1993. Again, while the companies range similar in terms of other features, Microsoft BI is cost-effective.

ThoughtSpot

This is also a similar company that develops software related to business intelligence. The company has its base in Sunnyvale, California. In comparison with Power BI, Thoughtspot seems to be less cost-effective as the former provides free-to-use methods and monthly payment subscriptions too. Along with this, customizing the reports and dashboards feature is available in Microsoft BI only

Dash Enterprise

This is a company that aims to provide software solutions to its customers in the field of business intelligence. As Dash Enterprise and Microsoft BI provide software for business intelligence, they have similar features. Besides a major difference between the two is that you can create reports and the dashboard are visually more attractive.

Sisense

Furthermore, the Sisense company was founded in 2004 and has many offices in various parts of the world. It is a business analytics software company providing products in that field. Although, both Sisense and Power BI are business intelligence software solutions so they have similar features. But the basic advantage the latter has on the former is that Power BI provides trend indicators that help businesses to recognize the changing business patterns. This in turn helps them evolve better.

Oracle Analytics Cloud

This is a flexible public cloud service that provides a set of capable options to work with. It forms collaborative analytics like the Power BI. But in comparison, the latter seems to be cost-effective again.

Conclusion

Thus, you can see that Microsoft BI among different data analytics tools, provides similar features and capabilities in comparison to other business intelligence tools at a cheaper rate

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