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What is Data Observability? Lets understand Data Observability and Why it is Important. What is Data Observability? Data observability is an organization’s ability to fully quantify the health of the data, proactively detect issues and quickly apply a mitigation plan before issues become a factor in lost revenue, ROI or branding. Data is the lifeline […]

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 as Snowflake, Redshift, and Databricks, data load processes have become increasingly distributed and complex. Organizations are investing more capital in […]

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 databases such as Snowflake, Redshift, or Azure. Most companies’ data landscapes include development, QA, and production database instances. Data […]

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 the reality we know as data vulnerability, it is not the […]

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. The data is constantly shifted from source to source, often […]

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 collateral to create competitive advantage. This evolution has happened due to the fact that enterprises are becoming increasingly […]

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’s show is a production that has a […]

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, creating confusion among end-users and building a lack of trust in data. Therefore, it is […]

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 or find the origin of data and creates lots of misunderstanding that results in misinformed […]

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 context to data so the user can easily search and understand the data better. Users can […]

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 effectively. They are unable to find high-quality and trustworthy data to drive smarter […]

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 business value. A data catalog maintains an inventory of data assets through the discovery, description, and organization […]

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 across different analytics initiative across a company makes reconciliation process even harder. Another challenge stems […]

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 amount of time and money. Improved data accuracy—and as a result, improved reconciliation accuracy—correlates directly with reducing risk. This can make […]