Automatic Data Reconciliation, Data Quality, and Data Observability Automating Data Reconciliation, Data Observability, and Data Quality Check After Each Data Load Over the last several years with the rise of cloud data warehouses and lakes such ...
DataOps -Schema Compare, CI/CD, and Database Change Deployment
DataOps — Schema Compare, CI/CD, and Database Change Deployment for Snowflake, Redshift, Azure, and other databases. DataOps and CI/CD with respect to database schema compare and change deployment is a critical task, mainly when it comes to database ...
Is Your Data Vulnerable: 5 Questions for Better Data Security
When you think of data security and data vulnerability, what kind of images instantly spring to your mind? Do you instantly think of some sitting in a darkened basement, hacking the newest data stack on the block? While data hacking is one side of th ...
Data Monitoring for Marketing: Getting The Most Out of the $105 Billion Market
In this day and age of online presence building and digital marketing, data teams operate in data stacks that neatly set aside the relevant data in relevant fields. But that is not where the simplicity to the system ends. This is only where it begins ...
Data Reconciliation for Data Oriented Enterprises: Here’s Why
Data Reconciliation for Data Oriented Enterprises In a world that is increasingly dependent on how data impacts the enterprise’s bottom lines, we are constantly collecting data, collating it, cleaning it and finally merging it with our own collatera ...
How can Data Quality Make or Break Your Business Success?
How can Data Quality Make or Break Your Business Success? Whether you are running a business, or you are heading a division or business arm of a larger enterprise, you know that you need more than an MBA to run a data team and prosper from it. Today ...
Data Surveillance and it’s Perks In the Era of Data and Digits.
Data goes a long way from the source system to reach the end-users. It takes a lot of ETL (extraction, transformation, and load) to transfer data from one database to the other and then finally reach the analytics platform to be delivered to the end- ...
What is Data Reconciliation?
When the data migrate from source systems to a target analytics platform, it goes through several transformation steps. Many times, even though ETL jobs run successfully, due to one or other reasons data between source and target do not match, creati ...
How Data Linage Helps?
How Data Linage Helps? In a complex modern data environment, understanding end-to-end data is a very big challenge. With the rapid adoption of data analytics, data flows in many directions across the business – this makes it difficult to understand ...
How Data Catalog helps?
How Data Catalog helps? The data catalog allows the user to do a google-like search to discover data and reports. With our data linage capabilities, physical data assets are classified and linked to data domains and attributes adding business contex ...
Why Data Catalog?
Why You Need A Data Catalog In today's environment data is produced, stored, and consumed at a rapid pace. All these data are stored in numerous systems. In this data chaos, Organizations struggle a lot to organize, maintain and use their data eff ...
Defining Data Catalog
Defining Data Catalog? A Data Catalog is a collection of metadata combined with data management and search tools that empowers business users to quickly discover and understand data that matters so they can generate impactful insights that drive b ...
Challenges associated with continuous data reconciliation processes
Data reconciliation is a critical component for any company, but the inability to fully automate it is a challenge that often requires hundred hours of manual effort and nevertheless loss of productivity of not able to access data on time. The costs ...
Data Reconciliation Defined
Before we dive into the world of data reconciliation, let’s start with a definition. Data reconciliation is the method of verifying and validating data collected from multiple systems, and is required to ensure that data is moving from system to syst ...
Real Challenge of Reconciliation
Often organizations deal with two general types of reconciliation: record count matches and values matches. Record Count matches: This type of reconciliation deals with matching records in source vs target and alerting when counts goes suddenly hi ...
What Makes Digital Transformation of Reconciliation Challenging?
Eliminating costly, time-consuming, manual tasks from the reconciliation process is not as easy as it sounds. The primary roadblocks are diverse set of source system and diverse set of technologies. On top of it not able to have holistic approach acr ...
Recognizing the Importance of Efficient, Accurate Reconciliation
Accurate Reconciliation Improved reconciliation processes lead to reduced risks and costs and can translate into increased end users’ satisfaction. Less effort spent on manual processing, research and other forms of intervention saves a significant ...
The Promise of Accurate, Effective Reconciliation
There is a better way. Reconciliation systems are evolving and becoming capable of ingesting multiple formats and unstructured data, handling complex data transformation and reconciliation with intelligent matching capabilities, enabled through machi ...