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How to Upgrade a Database of the Large Enterprise System

An outdated database is problematic for enterprise business processes.

This engine powers the whole system. Hence, it requires regular and proper maintenance — database migration, which improves data accessibility and integrity. Here is a look at how our team handles the task; discover how to upgrade a database with a smooth transition.

About the Client

A global provider of insurance services in a booming and dynamic healthcare sphere approached ModLogix to update its databases. The firm’s software helps healthcare facilities with financial management. As such, the software processed terabytes of data daily, while the volume of data received was on the rise. Particularly, the client dealt with Big Data, operating data massif from different sources.

Their preliminary inquiry was to improve data management, as Microsoft SQL Server 14 database could no longer handle the large system’s workloads. From the financial perspective, the client also planned to reduce the cost of data storage and compute. But during our cooperation, the company acquired a new business entity, and a new task arose — database integration.

The Business Context

Strategic business decisions always back up any drastic technological changes. In this case, merging a used system with the existing platform caused a new round in the company’s IT strategy.

The merger and acquisition process

The merger and acquisition (M&A) process involves a lot of challenges at business and organizational levels, and there is the tech part as well.

In the meantime, they need to integrate different systems under one roof to get a centralized view over all processes.

From the very beginning, the company went through numerous steps:

Pre-merger assessment
Audit
Merger planning
Performance analysis
Implementation

The M&A goal was:

To diversify company’s services

Increase its market share

But the road wasn’t so smooth.

Challenges We Faced in This Project

Integration shortfalls and data issues are considered the most dangerous risks during the merger process.

The answer contained the main challenges

Conduct data migration and standardization

The global aim was to reach a synergy of unified systems and align business processes. To that end, we had to carefully analyze the data, unify it, and upgrade the database to Microsoft SQL Server 17 as was initially planned. This bunch of work required solid expertise, which our team already had.

Preserve data security

As the client worked in a highly regulated industry, we had to handle the sensitive data carefully. In this regard, our team had to investigate and identify the particular cybersecurity and data privacy risks.

Provide data compliance

Healthcare and financial sectors put forward strict regulations; it was crucial to ensure compliance with specific security standards and controls.

The Difference in Data Processing Schemes

The core SaaS-based system had an automated data processing feature that wasn’t presented in another system.

Needless to say, data architectures were also completely different, so we needed to resolve the question of how to merge databases with varying formats of data and sources to support the M&A process.

The Importance of Planning and Risk Management During the Migration Process

Finally, we moved to the most important part of every software modernization project. Planning! At this stage, we set a timeline and the resources needed for the project in a database migration plan document.

Since ModLogix was a tech partner in the M&A deal, our dedicated business analyst was fully involved in project execution. He read into incomplete documentation, got into business processes, and interpreted the requirements. That information was directly implemented in data standardization; plus, it enabled us to eliminate duplications and critical errors.

In line with database migration best practices, we planned for a homogeneous migration. MS SQL Server was an excellent fit for the client’s needs, and we had to select a new appropriate version. When everything was clear, we started the data transformation process.

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Working on Different Data Formats: What is Data Unification?

The target and acquired system had nothing in common; in fact, the acquired software was supposed to become a new module in the larger SaaS platform. But unfortunately, these systems captured, processed, and managed data differently.

In order to consolidate all of the organization’s data into a single source, our team took up a data unification, a process of structuring raw data from multiple streams, including incomplete or siloed data sets. The data unification process included:

Analyzing an acquired system

Describing and interpreting data sources, identifying legacy and unused data.

Ingesting the data

Moving the data from an acquired system to the target one and data warehouse.

Data cleaning

Getting rid of legacy data that has no value for current business processes.

Deduplication

Identifying and deleting extra copies of data.

Classification

Distributing acquired data according to its type, sensitivity (high/medium/low), and value for the company.

Exporting the data

The New Data Architecture

When performing it, we built a new data architecture aligned with the organization’s needs and flexible enough to support future business growth.

How to Do Database Migration: Experts Advice

There’re 2 common scenarios of database migration.

In this case, we dealt with a homogeneous migration — SQL Server database migration version 14 to 17.

In order to get this process right, let’s recall the fundamental principles of Database Management Systems (DBMS) and relational DBMS (RDBMS) in particular.

Nowadays, relational databases are used in the majority of current IT systems.

They are prevalent among organizations due to their manageable and flexible nature.

Relational DBMS store data in rows and columns, organized in multiple tables (‘relations’).

However, few know that relational databases were invented in 1970 by computer scientist Edgar F. Codd. He proposed a statute, “Codd’s Twelve Rules,” to create an appropriate and functioning system.

MS SQL server migration steps

The old but golden rules formed the basis for our data migration project. Following the database migration best practices, we established the process of moving to MS SQL Server 17:

Assessment and planning

Discovering existing data sources and functionality, scanning SQL instances. While understanding the source database, we evaluate the complexity of the whole migration.

Data encryption and backup

Then, we took another necessary step, an encrypted backup, the process of data preservation. All sensitive data, including protected health information (PHI), must be encrypted for security.

Migration execution

Data normalization. The migration follows 3 steps, and the data normalization was the first one. The process involves organizing data into tables to reduce data redundancy and inconsistency.
Data denormalization. The next step was to denormalize data according to best practices for managing relational databases. The essence of the process is to add redundant copies of data to speed up its retrieval.
Data extraction and transformation. Then, we exported data from the current database to the target SQL Server database.

Test migration

Working on data migration, we kept testing the data until the upgraded database version became stable and consistent, including fixing discrepancies

It's worth remembering

Leading experts from ModLogix recommend keeping balance in normalized and denormalized schemas for modeling data. However, too much database normalization can also be destructive to the system’s performance as a level of normalization must match the database structure. To make it right, consult with proven DB experts.

SQL Server: Release Features

SQL Server 2008 Policy-based mgnt. Programmability

SQL Server 2008 R2 PowerPivot (In-Memory) Policy-based mgnt. Programmability

SQL Server 2012 AlwaysOn In-Memory ColumnStore Data Quality Services Power View Cloud

SQL Server 2014 In-memory across workloads Hybrid cloud optimized HDInsight service Cloud BI

SQL Server 2016 Industry leading performance Built-in ML Hybrid cloud optimized Cloud Engineering First Cloud BI

SQL Server 2017 Industry leading performance Graph DB Built-in ML Choice of language & platform Easy migration to the cloud

SQL Server 2019 Industry leading performance ML-enabled perf & security Built-in ML Choice of language & platform Lift & shift to the cloud

Get a FREE consultation from our certified database developer regarding your legacy database migration

Official SQL Server
Support End Dates

What end of support dates for SQL Server? SQL Server, developed and marketed by the technology giant Microsoft, has been constantly evolving since 1989. Microsoft adds innovative and useful features to each release. So when one version is about to expire, organizations can easily move to the stable one.

In addition, Microsoft even announced regular Patch Tuesdays starting in 2003 to distribute fixes for software products. However, officials advise companies to monitor their current SQL Server status and stick to the latest releases.

Version Release year Mainstream Support end year Extended Support end year

SQL Server 2019 2019 2025 2030

SQL Server 2017 2017 2022 2027

SQL Server 2016 2016 2021 2026

SQL Server 2014 2014 2019 2024

SQL Server 2012 2012 2017 2022

SQL Server 2008 R2 2010 2012 2019

SQL Server 2008 2008 2012 2019

SQL Server 2005 2006 2011 2016

SQL Server 2000 2000 2005 2013

Do you want to get the MS SQL Server migration checklist to plan your next migration project?
Download your personal template.

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Business Value of Data Migration during the Merge and Acquisition Process

In this case, data migration was driven by a company’s growth, and our team was in charge of supporting the tech part. With more than 80% of all mergers and acquisitions failing, among other things, due to data migration issues, our team was focused on eliminating business disruptions.

We develop KPIs (at each tier) for effective transition, allow systems to co-exist, and educate the users on the new functionality. These steps were crucial for the company to continue stable work.

SCOPE OF WORK :

1 Project Manager

1 QA Engineer

1 Business Analyst

2 weeks

3 Database Developers

Results

2x increase in system’s performance

The transition to the new MS SQL Server allowed the system to process the data volumes much faster. In addition, optimized SQL queries provide lower execution time, resulting in lightning-fast software responses to users.

Lower costs of ownership

New MS SQL features, including automatic database tuning, smart differential backup, and security enhancements, significantly reduced the general expenses on maintenance. Simply put, developers spend less time on fixing bugs and introducing modifications.

Higher ROI and better business continuity

Due to the timely software upgrade, our client not only cut its IT budget on maintenance but also received high satisfactory rates from the end-users.

Acquiring the new market share

As the M&A deal and data standardization process went successful, the company expanded its product line and, as a result, generated additional revenue.

Results