IIS Tool Suite Overview
As per a study conducted by a leading market research and advisory company the data that we have generated in the past two years is many times more than that we generated in over two decades. It has not just multiplied, but have also become complex, varied and is being generated at much more rate than it ever was. These factors present a data integration challenge to the industries and businesses to be able to better
Teradata – Overview
PowerCenter works with many databases, among which Teradata is one of a kind. Informatica PowerCenter integrates Teradata database into any business system and it serves as the technology foundation for controlling data movements. In Informatica PowerCenter, ODBC is used to connect with Teradata tables and its data.
This blog helps you to create, configure, compile, and execute a PowerCenter workflow in Windows that can read the data from and write the data to Teradata database.
This blog post section gives an overview of GDPR, requirements, impact on business, common challenges faced by organizations and next steps recommended for GDPR compliance.
The General Data Protection Regulation (GDPR), enacted in April 2016 in Europe, will come into effect globally on May 25, 2018. The objective of GDPR is to provide a cohesive privacy law for companies and increased data protection for EU citizens (Subjects). GDPR regulates how EU residents’ personal data is collected, processed, stored,
Data is siloed across wide variety of platforms in an enterprise environment and the data needs to be processed, cleansed, and mastered to ensure it is same across source systems for effective reporting and analysis. To cater to this need, Informatica provides Master Data Management (MDM) product called Multi-Domain Edition (MDE). To master the data in this tool, the data needs to be loaded into the Informatica MDM Hub. In Informatica MDM data can be loaded in two different
Data Quality is the buzz word in the digital age.
What is data quality and why is it so important?
“Data quality” is the term that is probably hidden but plays an important role in many streams. Data plays a vital role in acquiring a market place, especially in enterprise data management stream.
Data Quality Examples
Following are some examples which emphasize the need for data quality.
- A customer shouldn’t be allowed to enter his age where he
Data Quality – Overview
Corporates have started to realize that Data accumulated over the years is proving to be an invaluable asset for the business. The data is analyzed and strategies are devised for the business based on the outcome of Analytics. The accuracy of the prediction and hence the success of the business depends on the quality of the data upon which analytics is performed. So it becomes all the more important for the business to manage data as
Data Generation, Analysis, and Usage – Current Scenario
Last decade has seen an exponential increase in the data being generated from across traditional as well as non-traditional data sources. International Data Corporation (IDC)report says that, data generated in the year 2020 alone will be a staggering 40 zettabytes which would constitute a 50-fold growth from 2010. The data generated per second has increased to 2.5 Quintillion bytes and with the advent of latest innovations like the Internet of Things; it
Web Services Overview:
Web Services are services available over the web that enables communication and provide a standard protocol for communication. To enable the communication, we need a medium (HTTP) and a format (XML/JSON).
There are two parties to the web services, namely Service Provider and Service Consumer. A web service provider develops/implements the application (web service) and makes it available over the internet (web). Service Provider publishes an interface for the web services that describes all the attributes of
MongoDB is an open-source document- oriented schema-less database system. It does not organize the data using rules of a classical relational data model. Unlike other relational databases where data is stored in columns and rows, MongoDB is built on the architecture of collections and documents. One collection holds different documents and functions. Data is stored in the form of JSON style documents. MongoDB supports dynamic queries on documents using a document based query language like SQL.
This blog post
This blog post is the final part of the Data Warehouse Migration to AR series. The second part of the blog post series Data Warehouse Migration to Amazon Redshift – Part 2 details on how to get started with Amazon Redshift, the business and technical benefits of using AR.
1. Migrating to AR
The migrating strategy that you choose depends on various factors such as:
- The size of the database and its tables
- Network bandwidth between