Data Modernization Services

In the words of great American writer Daniel Keys Moran, “You can have data without information but you can’t have information without data.” First the question arises what is data modernization?

In simple words it is the process of using the company’s existing database(legacy systems) to more advanced and efficient systems mainly on cloud based platforms.

It helps in converting the organization’s data into more usable formats for the modern workplace. It includes data integration, cleansing, consolidation, transformation and migration.

Let’s know more about the challenges that we face in the legacy systems to understand why we need Data Modernization so badly?

Out Technology – The main problem is that the legacy systems are out of date technology making it challenging to keep up with the modern day advancements.

Security Vulnerabilities- The legacy systems are more prone to cyber attacks as they lack the latest security features making them more susceptible to attacks and putting sensitive data at risk.

High maintenance Cost – Maintaining physical servers are more hectic to maintain and also the costing to maintain the physical servers running is very high as compared to doing the same on cloud platforms.

These are some of the major issues faced by the legacy systems and the organizations face themselves in quite a dilemma to change into other modern solutions as they already invested quite a lot in the past.

Let’s now discuss the key drivers for data modernization.

Data Integration – Data is frequently scattered around different data storages around the globe. In this regard data integration helps in collecting data from various sources like CRMs, supply chains, APIs, etc. and bringing them at one place for comprehensive analysis.

Data Quality – Data modernization includes cleansing of data to ensure better data quality. It includes removing duplicates, fixing errors, standardizing formats, and verifying data accuracy.

Data Warehousing – This component offers a centralized repository where enterprises store their both unstructured and structured data for reporting or analysis purposes.

Cloud Computing – Big data and cloud computing are the main components of data modernization strategies.

It offers flexibility and scalability. Moreover, it is highly cost-effective when it comes to handling large data volumes.

It involves solutions like NoSql and hadoop that allow the processing and analysis of unstructured and diverse data like sensor data, customer interactions, and much more.

So now what after the data modernization? How will it impact your business ?

Improved Decision Making – Modernized data platforms provide various real-time data insights for effective decision making faster. Legacy systems often store false or dummy data which makes the accessing of information and implementing less effective and efficient.

Fostering Innovation – With a whole modernized data structure, organizations can experiment with new technologies like IOT, AI, and blockchain which were difficult earlier with legacy systems.

Operational Efficiency – Modern data solutions provide storing large volumes of data whether it is structured or not easily and similarly it is easy to analyze that data as it has already been cleansed and filtered which ultimately enhances your performance and improves time efficiency.

There are many real world examples of companies which used these technologies and improved their customer feedback and the complete data infrastructure and handling.

For example – Netflix, General Electric, Coca Cola, etc.

Our Services

Migrating Data – Migrating data from outdated legacy systems or on premises to cloud based data warehouses.

Real-time data Processing – Real time data processing pipelines to support advanced analytics and machine learning.

Redesigning Data – Redesigning data architectures to optimize performance, scalability, and integration.

Seamless Integration – Seamless integration of data from various sources breaking down data silos.

Why Choose Us

Expertise :

1. Industry Expertise
2. Proven Track Record

Data pipelines :

1. Production-grade Pipelines
2. Apache Kafka
3. Amazon Kinesis
4. Google Dataflow
5. Apache Spark
6. Databricks

Robust Analytical Solutions :

1. Google BigQuery
2. Tableau
3. Power BI
4. Looker