Itamar Ben Hemo

With 2020 fast approaching, it’s a good time to think about how data management will evolve.

The  growth of cloud services over the past five years has changed the way we interact with data – from storage to management to processing to visualization. The growing appetite for more and better data, means that processes can get tricky and messy if not managed correctly.

It’s easy to boil down the industry’s biggest necessity to a single word: simplicity.

Simplicity will always be a driving force for everything we create at Rivery. We help companies build a serverless data pipeline. This eliminates the need to spend time & resources orchestrating data processes.

These are three important areas in which we’ll help simplify and improve data management processes in the upcoming year:

 

Data Centralization:

Centralizing and connecting all data sources for an organization’s entire data operation is something which any data engineer strives for.

As companies grow, it’s normal that they make ad hoc data connections and fix short-term problems.

But with multiple teams needing to access & connect different data sources, databases, and insights, a chaotic data infrastructure that isn’t streamlined is a ticking bomb. In the long-term, things will get very complicated, very fast. 

The cost of not streamlining a data pipeline and centralizing data processes goes beyond time and effort.

It has a direct impact on the cost of running a business – and more importantly, on the breadth and quality of the insights that an entire organization will have access to.

 

Moving from ETL to ELT:

ETL processes are becoming less relevant and effective. Before the cloud, it made sense when taking into account the traditional rigid infrastructures and data centres.

For companies managing large data sets, the loading process can take hours and even days. 

ELT makes the most of the cloud, helping organizations of any size operate in a much more agile way. It empowers companies to analyze larger pools of data without the constraints of maintenance or lengthy waits.

As businesses move to real-time or near real-time analytics, the future of data warehousing need to be more agile than ever before. 

The old ‘ETL’ chain of events makes it very hard for data analyst who need to somehow predict or guess how data will be used before reports are created.

When changes are needed, the need to reverse-engineer the operation can become costly and time-consuming. Moving to an ELT process won’t be a luxury but a necessity.

 

Continuous data migration:

When moving from on-premise legacy systems to the cloud, companies need to migrate their entire database to a new data repository or data warehouse.

Keeping databases up to date is hard and time-consuming when they are constantly evolving with updates and changes. This creates operational bottlenecks and friction between analytics teams and operational data teams, who are often in charge of maintaining the original database. 

Rivery’s upcoming CDC feature (change data capture), is specifically designed to increase efficiency and productivity by removing these unnecessary processes.

There’s no need for maintenance since data is continuously fetched from logs and up to date with a serverless data pipeline that doesn’t require upkeep.

What’s more, changes to the original tables in the database are reflected automatically and in real-time on the target table, removing the need to add or maintain incremental fields – and improving overall data quality.

And since the flow is now a continuous stream, it becomes exponentially quicker to pull or export data (and metadata).

If you are migrating applications to the cloud, you don’t just want to turn them off. Unfortunately migrations don’t just happen instantly.

Since it is not viable to stop people from using the application during the migration process, the data likely has changed by the time the migration has finished.

To ensure that the on-premise and cloud database remains identical during this process, Rivery’s CDC feature will track changes in the on-premise database and apply this to the cloud.

This becomes extremely important because it can take weeks to even months to confirm the migration was successful.

We look forward to working together in the new year!

Time to Ride the River

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