Featured Post

Step-by-Step Guide to Creating an AWS RDS Database Instance

-
Image
 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...
Post a Comment

QlikView Server vs Publisher Top Differences Really Useful to Your Project

-

The differences between QlikView Server and publisher, I have given for your reference. These are related to internally how differ each other.




QLIKVIEW SERVER


  • The QVS is a server-side product. It contains an in-memory analytics engine, which handles all client/server communication between a QlikView client (Desktop, IE plugin, AJAX, or Mobile) and the server.
  • The Administrator can have access to the management console to control all aspects of the server deployments (including security, clustering, distribution, etc.) 
  • It also includes a web server to provide front-end access to the documents within.
  • The web server’s user portal is known as Access Point. (It’s important to note that while the QVS contains its web server, one can utilize Microsoft IIS (Internet Information Server) for this purpose, too).
  • The QVS handles client authorization against existing directory providers (Microsoft Active Directory, eDirectory)
  • It also performs read and write to ACLs (access control lists) for QVW documents.



QlikView Server vs Publisher
Qlikview

QLIKVIEW PUBLISHER


  1. The QlikView Publisher is a server-side product.
  2. It can use to load data directly from data sources defined via connection strings in the source QVW files. 
  3. It is also used as a distribution service to reduce data and applications from source QVW files based on various rules (such as user authorization or data access privileges) and to distribute these newly-created documents to the appropriate QlikView Servers or as static PDF reports via email.
  4. Data sources that you can access in QlikView are standard ODBC (OLEDBcompliant databases), standard flat files ( Microsoft Excel and XML), and from systems such as SAP NetWeaver, Salesforce.com, and Informatica.

Keep Reading

Comments

Post a Comment

Thanks for your message. We will get back you.

Popular posts from this blog

Step-by-Step Guide to Reading Different Files in Python

-
Image
 In the world of data science, automation, and general programming, working with files is unavoidable. Whether you’re dealing with CSV reports, JSON APIs, Excel sheets, or text logs, Python provides rich and easy-to-use libraries for reading different file formats. In this guide, we’ll explore how to read different files in Python , with code examples and best practices. 1. Reading Text Files ( .txt ) Text files are the simplest form of files. Python’s built-in open() function handles them effortlessly. Example: # Open and read a text file with open ( "sample.txt" , "r" ) as file: content = file.read() print (content) Explanation: "r" mode means read . with open() automatically closes the file when done. Best Practice: Always use with to handle files to avoid memory leaks. 2. Reading CSV Files ( .csv ) CSV files are widely used for storing tabular data. Python has a built-in csv module and a powerful pandas library. Using cs...
Read more

SQL Query: 3 Methods for Calculating Cumulative SUM

-
Image
SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences. Using Window Functions (e.g., PostgreSQL, SQL Server, Oracle) SELECT id, value, SUM(value) OVER (ORDER BY id) AS cumulative_sum  FROM your_table; This query uses the SUM() window function with the OVER clause to calculate the cumulative sum of the value column ordered by the id column. Using Subqueries (e.g., MySQL, SQLite): SELECT t1.id, t1.value, SUM(t2.value) AS cumulative_sum FROM your_table t1 JOIN your_table t2 ON t1.id >= t2.id GROUP BY t1.id, t1.value ORDER BY t1.id; This query uses a self-join to calculate the cumulative sum. It joins the table with itself, matching rows where the id in the first table is greater than...
Read more

PowerCurve for Beginners: A Comprehensive Guide

-
Image
PowerCurve is a complete suite of decision-making solutions that help businesses make efficient, data-driven decisions. Whether you're new to PowerCurve or want to understand its core concepts, this guide will introduce you to chief features, applications, and benefits. What is PowerCurve? PowerCurve is a decision management software developed by Experian that allows organizations to automate and optimize decision-making processes. It leverages data analytics, machine learning, and business rules to provide actionable insights for risk assessment, customer management, fraud detection, and more. Key Features of PowerCurve Data Integration – PowerCurve integrates with multiple data sources, including internal databases, third-party data providers, and cloud-based platforms. Automated Decisioning – The platform automates decision-making processes based on predefined rules and predictive models. Machine Learning & AI – PowerCurve utilizes advanced analytics and AI-driven models ...
Read more