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Many tools can do interactive data analysis. I can list some: R, Matlab, esProc, SAS, SPSS, Excel, and SQL,etc. But for easy to use, esProc is the best. I can list you some reasons.
SQL is the most widely used structured data query and analysis language. Tts syntax is close to that natural language and easy for programmers to learn. But not easy for analysts without high technical background. Besides, it can't make three-like step by step computing. Excel is liked by many people due to its convenience. But for complex data computing and analysis, Excel is not great enough. R is good for its agile syntax but requires strong technical background. Similar to R, Matlab also has good scalability but needs high strong technical background. SAS has powerful capabilities in chart plotting for in-depth applications but is still less friendly than other analysis software. SPSS has a powerful graphic user interface. But its syntax is fairly poor and is incapable for the free analysis other than the fixed algorithms. The menu-style interface is inconvenient for stepwise computation.
esProc is a script with an expert in interactive analysis on structured data. It supports free data analysis, requiring relatively low degree of technical background. Its syntax is agile and easy-to-use. Excel-style interface makes it good for complex data processing and step by step computing. Also, it doesn't need pre-modeling. Only disadvantage is lacking of the fixed algorithm and functions specific to some industries, such as correlation analysis or regression analysis.
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Does data warehouse contain data?
Warehousing term is used whenever it is about something to be stored in great quantity with proper categorisation for easy accessibility in need; same applies for data warehouse. It only gets in dept in case of data; relevancy, timeliness and analysis followed by reporting are of prime importance. Source(s): http://bit.ly/153rq7v
What are the reasons for creating a data mart?
Data marts are created for various reasons. They're easy to access, easy to create, create collective views for groups, is not cluttered, and cost less to implement than a data warehouse.
How can a bar graph help?
it can show data easy to compare
What is a data table used for?
A data table is used to organize and display information that are gathered.
How is a graph similar to a data table?
A graph is similar to a data table in that they both present the data. A difference is that the graph is more of a visual representation. Often, trends in the data are easy to recognize in the visual representation of the graph.
Please recommend an interactive application for data analysis?
Hi, everybody, please give me some advice I need to conduct a large amount of data analysis on database. Could anyone recommend an interactive application for data analysis? The requirements are: 1. Able to cope with the unexpected requirement rapidly. 2. Able to perform further computations on results interactively. 3. Easy to confront even a large amount of complex computations What would you great expert recommend? Thanks in advance.
Why is some data coded for storage as text in database?
Storing data as text in a database allows for easy manipulation and querying using text-based functions and tools. It also provides flexibility in terms of accommodating different data formats and structures. Additionally, text data is human-readable, making it accessible for analysis and reporting purposes.
What are Interactive query facilities?
Interactive query facilities refers to management programs which make it easy to support multiple time-varying attributes at ago. These are used in database programming and ensure that reports are made with minimal data processing.Ê
Clear guidance on data analytics tools?
Certainly! Data analytics involves using various tools and software to collect, clean, analyze, and visualize data. The choice of tools depends on your specific needs, skill level, and the type of data you are working with. Structured Learning Assistance - SLA is known for its excellence in education sector who provides Data Analytics Course in Delhi fortified with a well established infrastructure with advanced lab facility, senior industry expert and modern training system to enhance the knowledge of students. SLA is well known entity having Data Analytics Institute. It is built with all convenient facilities and positive study ambiance for the students. Fulfill the main task of placement, SLA aids in 100% Job Placement after completion of 70% course. Here's a breakdown of some popular data analytics tools and their key characteristics: 1. Microsoft Excel: Best For: Beginners and basic data analysis tasks. Key Features: Spreadsheet-based tool, widely used for data cleaning, basic analysis, and simple visualizations. Pros: User-friendly, readily available, and suitable for small to medium-sized datasets. Cons: Limited for complex or big data analysis. 2. Python: Best For: Data scientists, analysts, and those requiring flexibility and scalability. Key Features: Offers various libraries (e.g., Pandas, NumPy, Matplotlib) for data manipulation, analysis, and visualization. Pros: Highly versatile, extensive libraries, open-source, and suitable for handling large datasets. Cons: May require programming knowledge. 3. R: Best For: Statisticians and data scientists. Key Features: Comprehensive statistical analysis and data visualization capabilities. Pros: Strong statistical packages, extensive community support, and a wide range of packages for specialized tasks. Cons: Steeper learning curve for beginners. 4. SQL (Structured Query Language): Best For: Database professionals and analysts working with structured databases. Key Features: Designed for managing and querying structured data in relational databases. Pros: Efficient for data retrieval, manipulation, and aggregation. Cons: Primarily suited for structured data. 5. Power BI: Best For: Business analysts and professionals for data visualization and reporting. Key Features: Provides interactive data visualizations, dashboards, and easy data connectivity. Pros: User-friendly, integrates with various data sources, and excellent for creating reports and dashboards. Cons: Focused on visualization and reporting, less suitable for advanced analysis. 6. Tableau: Best For: Data analysts, business intelligence professionals, and data visualization experts. Key Features: Offers advanced data visualization and interactive dashboards. Pros: User-friendly, excellent for creating interactive and shareable visualizations. Cons: Premium versions can be expensive. 7. SAS (Statistical Analysis System): Best For: Enterprise-level data analytics, especially in regulated industries. Key Features: Offers a comprehensive suite for data analytics, reporting, and machine learning. Pros: Trusted in industries with strict data governance requirements, robust statistical capabilities. Cons: Can be costly and has a steeper learning curve. 9. Alteryx: Best For: Data blending, preparation, and analytics. Key Features: Offers a user-friendly interface for data cleaning, blending, and advanced analytics. Pros: Easy to use, excellent for data preparation, and integrates with various data sources. Cons: Can be expensive for some users. 11. Hadoop and Spark: Best For: Big data analytics, distributed computing, and data processing. Key Features: Scalable, distributed platforms for handling large datasets and performing advanced analytics. Pros: Scales to handle big data, supports various programming languages. Cons: Requires a distributed computing infrastructure, more complex setup. Remember that the choice of a data analytics tool should align with your specific goals, the size and complexity of your data, and your skill level. It's often beneficial to be proficient in multiple tools to address different data analysis scenarios effectively. Additionally, many online courses and tutorials are available for learning and mastering these tools, making it easier to get started or enhance your skills.
What is a good tool for survey analysis?
Most survey analysis tools come in a integrated software package. They offer quick results and easy step by step instructions on how to"drag and drop" the survey information into categories.
How does atlas works?
Atlas is a cloud-based data visualization tool that helps businesses create and share interactive charts and graphs. Users can upload their data, choose the type of visualization they want, customize it with various styling options, and then embed or share the interactive chart. It allows for easy data exploration and interpretation, making it a popular choice for data analysis and reporting.
What is executive information system and what are its characteristics?
Characteristics of EIS: ->Drill down ->summarized data -> Easy Analysis -> Exceptional Reporting -> Navigation of information
How would you define Microsoft exel?
A spreadsheet application tool that analyzes data in a table format using formulas. a software program that allows the easy analysis and manipulation of data using tables and formulas
What are the advantages of arithmetic mean?
It is easy to use in further analysis calculation can be done easily using arithmetic mean is unique value for each data set
Where can one learn more about product data management?
At Solidworks an online division of Dassault Systems you can learn about Product Data management. You can learn how it can help you as well as easy ways to implement these management tools.
How can I compile large amounts of customer data?
There are a number of programs on the internet that can collect data and compile data you input into a spreadsheet or other document for easy evaluation. One such program is "Track Source". Track Source is a online data collector and analysis tool which would be great for collecting and compiling customer data for your business.
What are some small interactive easy traveling pets that are easy to care for and are not hamsters or guinea pigs?
Ferrets are small and interactive, but they are not rodents, so you can't keep them in a cage all the time. They have personalities that are a cross between a dog and a cat.
