Key Takeaways from TEA Tarik Talk - ACL And ... Or Tableau?
Throwback -TEA Tarik Talk in ACL And ... Or Tableau?
We are proudly announcing it was a successful session not to be missed by Data Analyst professionals.
For those who did not manage to attend the conference, we have put together a handy recap of the key TEA Tarik Talk in ACL And ... Or Tableau? discussion points for you.
- Definition of data is - facts or information used usually to calculate, analyze, or plan something. See more meanings of data. How to use data in a sentence.
- Types of data:
- 4 Types of Data: Nominal, Ordinal, Discrete, Continuous
- Nominal - These are the set of values that don’t possess a natural ordering. Let’s understand this with some examples. The color of a smartphone can be considered as a nominal data type as we can’t compare one color with others.
- Ordinal - These types of values have a natural ordering while maintaining their class of values. If we consider the size of a clothing brand, then we can easily sort them according to their name tag in the order of small < medium < large. The grading system while marking candidates in a test can also be considered as an ordinal data type where A+ is better than B grade.
- Discrete - The numerical values which fall under are integers or whole numbers are placed under this category. The number of speakers in the phone, cameras, cores in the processor, the number of sims supported is some of the examples of the discrete data type.
- Continuous - The fractional numbers are considered as continuous values. These can take the form of the operating frequency of the processors, the android version of the phone, Wi-Fi frequency, temperature of the cores, and so on.
- What is data analytics?
Data analytics is the science of analyzing raw data to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.
- Definition of ACL Analytics
Audit Command Language (ACL) Analytics is a data extraction and analysis software used for fraud detection and prevention, and risk management. It samples large data sets to find irregularities or patterns in transactions that could indicate control weaknesses or fraud.
- Advantages of ACL
- Ease of use: Does not require high technical knowledge to use ACL Analytics
- Read-only Data: Once the data is imported into ACL, the user will not be able to edit or make changes to the records in the table. Other than that, the imported table does not affect the raw data (Data integrity).
- Function & Command: Plenty of useful commands to assist users in data analysis. Ex: DUPLICATE, GAP, JOIN, RELATE, SUMMARIZED.
- Ability to handle large amount of data: ACL has no limitation in terms of handling large datasets. It only depends on user’s hardware resources.
- Ability to integrate with different systems: ACL have most of database connector in the market that using ODBC. So, importing data from databases is seamless and secure when using ACL.
- Log file: ACL will capture all steps that user clicked. So, users won’t lose all your works. Log files also helps to ease the process of building automation.
- Tableau definition is - a graphic description or representation: picture. How to use tableau in a sentence.
- Advantage of using tableau
- Quick Visualization: Users can create an extremely interactive visual representation by using the drag and drop functions of Tableau.
- Comfortable implementation: There are various types of visualization options in Tableaus. This enhances the user’s experience. Tableau is easy to learn in comparison to Python. Those who don't have any experience or knowledge in coding, can also quickly learn Tableau.
- Mobile-friendly: There is an accomplished mobile app available for IOS and Android which adds mobility to Tableau users and allows them to keep statistics at their fingertips. The app supports the majority of functions that a desktop or online version has.
- Handle large datasets: Tableau can handle millions of rows of data with ease. Users can create different types of visualization, using large amounts of data, without disturbing the performance of the dashboards. Additionally, there is an option in Tableau that can go 'live' to connect with different data sources like SQL, etc.
- Data integration with different systems: The software supports establishing connections with many data sources, such as HADOOP, SAP, and DB Technologies, which improves data analytics quality and enables the creating of a unified, informative dashboard. Such a dashboard grants access to the required information for any user. Ref: https://help.tableau.com/current/pro/desktop/en-us/exampleconnections_overview.htm#
- Quick insights: The ability to develop a visualization by just applying the drag and drop method really helps the user to quickly understands the data.
- Concept of data access & data cleansing
- Analytic result workflow
a) List all you needb) Get the sense of the data structure (name of the table, fields….)c) Grab the relevant …select the initial data set (join of a table of data set)d) Play with the data (visualize your data, filter, comparison with another tablee) AHA – have a strong moment 0f complexity with your columns (what you need to add on in your visualization later)f) Share the insight (data that you applied can share with other departments)
- What is the difference? ACL Analytics and Tableau
- It has a difference. Not a competitor. It will complement each other with the data analytic process
- Enhance the user experience with the analytics capability.
- Centralized your analytics tools
- Can ensure ACL project to the tableau (no security issue)
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