Comparisons of OD, DW, DM

1. Create a table of comparisons for operational data, data warehouse, and data mart.

2. Describe the purpose of 3 tools and explain how it works. Include the advantages and disadvantages.

3. Research the role of business processes within an organisation and their function at different levels.

Comparisons of Operational Data, Data Warehouse and Data Mart
Operational Data	Data Mart	Data Warehouse
-The data that is been collected and analyze everyday -Day-to-day operation - overall but one day only (combination of any departments)	-   Data is from database -The information that they have is specific from one department saja - Data in a department - for a day only, a week, a month but for specific department only (categories)	- Accurate and appropriate data is being collected -    Data is being collected from different data mart - Organization system use to analyze data - contains different information from data mart

3 tools

Visualization

Sisense

MicroStrategy

Visualizations

Purpose

When the information is being presented, it makes the information easy to understand even for those people who are ot used to analyze data.

How it works

The visualization software pulls in data from these sources and applies a graphic type to the data.

Data visualization software allows the user to select the best way of presenting the data, but, increasingly, software automates this step. Some tools automatically interpret the shape of the data and detect correlations between certain variables and then place these discoveries into the chart type that the software determines is optimal.

Typically, data visualization software has a dashboard component that allows users to pull multiple visualizations of analyses into a single interface, generally a web portal.

Advantages of visualization

1 - Rapid Identification of Latest Trends

In this age, the volume of data that companies are able to gather about customers and market conditions can provide business leaders with insights into new revenue and business opportunities, presuming they can spot the opportunities in the mountain of data. Using data visualization, decision makers are able to grasp shifts in customer behaviors and market conditions across multiple data sets much more quickly

2 - Direct Interaction with Data

Data Visualization also helps the companies to manipulate and interact with their data in a direct manner. One of the greatest strengths of data visualization is how it brings actionable insights to the surface. Unlike one-dimensional tables and charts that can only be viewed, data visualization tools enable users to interact with data.

3 - Predictive Sales Analysis

With the help of real-time data-visualization, sales executives can carry out advanced predictive analytics for their sales figures, viewing up-to-date sales figures and see why certain products are underperforming and the reasons that sales are lagging. For example, discounts offered by competitors may be one of those reasons.

Disadvantages

1 - Data visualization tools show but they do not explain.

While data visualizations can be generated in real-time, they do not provide any explanations. In fact, the process through which companies draw insight has not changed in the last 30 years. Analysts look at data and then write reports. This process is too slow for the market and too costly for the company. At the same time, data visualization tools expect the user to be an expert in all of the data and all of the corporate best practices. Natural Language Generation (NLG) offers a solution adopted by many businesses. NLG automatically writes narrative explaining the insights and the drivers behind changes in the data. 

2 - No guidance

What if the user interpreting the data lacks expertise and/or training? He or she could make mistakes that may affect the entire company. At the same time, analysts could provide clients with incorrect or substandard advice. Even systems with Natural Language Query, expect the user to know what they are looking for. This works with simple data but the industry trend is towards big data, data lakes and complex analysis. It’s so complicated you might not even know what you don’t know, to paraphrase an American Defense secretary. The answer is so simple that its easy to miss. We don’t speak data, we speak English, so software that explains the data to us in plain English. This is the value of Natural Language Generation software, the last mile in the data analytics workflow.  

3 - Data visualization provides a false sense of security 

Graphics are great for conveying simple ideas fast – but sometimes, they are just not enough. If words could be replaced by pictograms, they would have been a long time ago. To express a complex situation, sentences and phrases are required along with a system that is smart enough to articulate   its reasoning process. Importantly, language also makes sure the end user really understands. Graphics can make users think they are making data driven decisions or think they fully understand the data when in reality they are only seeing a picture but they don’t know the full story.

Sisense

Purpose

- It enables user to easily share their insights with their team members and clients.

Sisense basically allows user to turn data into highly valuable insights and then share them with colleagues, business partners, and clients via interactive dashboards.

- It enables you to clean and consolidate data so you can explore and visualize it in a way that brings you valuable insights into your business.

How it works

It uses a Crowd Accelerated BI technology which can manage hundreds of queries simultaneously. Thus, Sisense allows users to collaborate in an accurate and real-time environment which ensures you get precise outcomes.

Advantages

1 - Gather all your information from all your sources and unify them into a single, accessible repository.

2 - Produce rich and intelligent analysis using robust visual reports without going through the hassle of preparation.

3 - Easily share your insights with your team, partners, and clients.

4 - Easy to use interface allows non-techies to quickly adapt and get acquainted with the system.

5 - Very fast system as it maximizes the potential of 64-bit computer, multi-core CPUs and parallelization capabilities.

Disadvantages

1 - Sisense is a “heavy” application. 

One of the common things we hear from prospective leads is that Sisense was too “heavy” for them. This is a statement on the power of server and the amount of space and resources taken up by the application, but also the amount of time needed for setup and configuration and user adoption.  Many prefer Yurbi for its simple install with a very easy operations and maintenance requirement.  And also the intuitiveness and simplicity of the Yurbi interface.  Even though Sisense has more features,  Yurbi is easier for their business users to adopt and all that is required.

2 - Sisense’s dashboards only interact on the web. 

The dashboard works great for those with real-time web access,  but to share a flattened, less feature-rich version that can be embedded or printed can cause a roadblock.  Sisense doesn’t offer powerful scheduled reports that can be sent via email so that users can consume reports outside of the online dashboard. Sisense users have complained to us about the lack of ability to share a report or offline dashboard via PDF with users outside of the Sisense system.

MicroStrategy

Purpose

To allows user to drill anywhere in the entire relational database, all the way down to transactional-level detail

How it works

It supports interactive dashboards, scorecards, highly formatted reports, ad hoc query, thresholds and alerts, and automated report distribution. Interfaces include web, desktop (for developers) and Microsoft Office integration. MicroStrategy Mobile also supports mobile BI.  

Advantages

1 – A wide range of visualization capabilities,

2- Provides small smart companies the ability to create snapshots of reports, allowing users to see how to change reports at over time.

Disadvantages

A significant decline in micro-business intelligence strategy is also pricing. Although it seems at first sight that the resolution of intelligence in small business is competitive, you will quickly find that the addition of all required units quickly raises the price to levels close to cognos and companies.

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