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Data Modernization

Modernization of the data warehouse includes technical practices, platforms, and tool types, as well as data analysis and governance to support data-driven business goals.

Modernization encompasses more transformative changes to applications, infrastructure, data, and business processes to prepare for and take advantage of the latest technologies.

data modernization services

Data modernization is the process of updating and improving an organization’s data systems and infrastructure in order to make the data more accessible, accurate, and useful. This can involve a variety of activities, such as converting legacy data into modern formats, implementing new data management technologies, and improving data governance processes. The goal of data modernization is to enable organizations to better utilize their data for decision-making and to support new business initiatives.

Modern data systems and technologies make it easier for users to access the data they need, when they need it, from any device or location. This can help improve productivity and enable users to make better decisions based on the most up-to-date information. Data modernization can help improve the accuracy and completeness of an organization’s data, which is critical for making reliable business decisions. With modern data systems and technologies, Data can be more flexible and scalable than legacy systems, which can enable organizations to quickly respond to changing business needs and opportunities.

The Advantage of
Managing Your Data

Improved Data Access

Easy access to data by users, enable users to make better decisions

Integrated Insight

Capture valuable insight and integrated database with other division

Data Driven Business

Judging the current situation by data and make a better decision 

Multipurpose Data

One data can be used for many purposes to get same undestatement

Analyze and Reporting

Modeling and visualizing data to stored in a dashboard for reporting

Planning and Projection

improve the accuracy and completeness of an organization’s data and data intelligent

Characteristics of Data

Precise and Accurate

Contain accurate information. Precision saves time for the user as well as their money.

Consistent and Reliable

Standard data format and consistent for many use and deliver reliable information

Relevant and Accessible

Relevant by user requirement. Easily accessible and could be processed further with ease.

Data Modernization Services

Big Data Migration

Data migration creates a competitive advantage by giving the ability to meet growing user demands for digital services and convenient interactions. Consolidate legacy systems to new applications dataset.

Data Warehouses

Achieve scalable computing and distributed storage capabilities with separated storage. To face growing data volumes improving the extensibility, stability, operability, performance, and resource utilization.

Data Analytics

Enable organizations to make more-informed business decisions. Analytics also enables organizations to respond quickly to emerging market trends and gain a competitive edge over business rivals and provide business executives with actionable information

Business Intelligence

Combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations make more data-driven decisions. prioritize flexible self-service analysis and speed to insight.

data modernization schema

Platform for Data

Data Warehouse

BigQuery, Cloud BigTable, Cloud SQL, Cloud Firestore, Cloud Spanner

Data Processing

DataFlow, Data Fusion, Data Prep, DataProc, VertexAI

Prediction & Insight

GKE, Looker, Data Studio

Data Visualization

Looker Studio, Tableau,

Pipeline Management

WorkFlows, Cloud Composer, Data Catalog, Cloud Run

Your Journey to Data-Modernization

Data Discovery

Focus on understanding the high-level data issues and goals, and brainstorm ideas about how to drive a better data architecture that satisfies business and application demands now and in the future.

Data Architecture

Design the overall architecture, including which clouds, technologies, and platforms to be used. Develop pipelines to ingest, transform and store data. implement the modern data architecture.

DataOps and Reporting

Define your data models, build dashboards with real-time refreshes and automate reporting. create predictable delivery and change management of data, data models and related artifacts.​

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