In business, sometimes it’s hard to see the forest for the trees. We work hard every day to meet our customers’ current needs and anticipate what they’ll want in the future. We listen carefully, attend to the market, and watch our cash flow. We impart our employees with the best training possible and benefits that inspire loyalty.
Growth and innovation are important, but big picture thinking can be really tough in this competitive world, especially when we are busy with day-to-day transactions and business is consistently good. But could business be great?
You outsource your IT services, Database Management and your web presence. It makes good financial and business sense to bring in the experts so you can focus on what you do best. A.D.S. is the provider of choice for big-picture organizational problem solving and creative growth strategy. We’ll help you think about your business in a whole new way, bringing a fresh perspective to long-standing challenges and helping you envision – and achieve – a future with unlimited possibilities.
Our objective is to build on your considerable strengths to ensure that together we become a force to reckon in this industry.
Data migration is the process of moving data from one location to another, one format to another, or one application to another. Generally, this is the result of introducing a new system or location for the data. The business driver is usually an application migration or consolidation in which legacy systems are replaced or augmented by new applications that will share the same dataset. These days, data migrations are often started as firms move from on-premises infrastructure and applications to cloud-based storage and applications to optimize or transform their company.
Types of migration:
• Storage migration. The process of moving data off existing arrays into more modern ones that enable other systems to access it. Offers significantly faster performance and more cost-effective scaling while enabling expected data management features such as cloning, snapshots, and backup and disaster recovery.
• Cloud migration. The process of moving data, application, or other business elements from either an on-premises data center to a cloud or from one cloud to another. In many cases, it also entails a storage migration.
• Application migration. The process of moving an application program from one environment to another. May include moving the entire application from an on-premises IT center to a cloud, moving between clouds, or simply moving the application’s underlying data to a new form of the application hosted by a software provider.
Basic Steps:
1. Extract data
2. Transform data
3. Load data
a high-level function that is responsible for the overall management of data resources in an organization, including: Database planning, analysis, design, implementation, and maintenance. Data protection. Data performance assurance. User training, education, and consulting support.
maintaining, securing, and operating databases and also ensures that data is correctly stored and retrieved. In addition, DBAs often work with developers to design and implement new features and troubleshoot any issues.
Database Design can be defined as a set of procedures or collection of tasks involving various steps taken to implement a database. Following are some critical points to keep in mind to achieve a good database design:
1. Data consistency and integrity must be maintained.
2. Low Redundancy
3. Faster searching through indices
4. Security measures should be taken by enforcing various integrity constraints.
5. Data should be stored in fragmented bits of information in the most atomic format possible.
Data designing illustrates the types of data that are stored in the system, the relationships between them and the ways that data can be grouped or organised. A data model is that blueprint or roadmap which facilitates a deeper understanding of the stored data.
What is backup and recovery?
Backup and recovery is the process of duplicating data and storing it in a secure place in case of loss or damage, and then restoring that data to a location—the original one or a safe alternative—so it can be used again in operations. Ideally, this backup copy (often called a snapshot) is immutable—meaning it cannot be altered after it is created to protect against mutations such as ransomware. Backup and recovery is also a category of onsite and cloud-based technology solutions that automate and support this process, enabling organizations to protect and retain their data for business and compliance reasons.
What are the 3 types of backups?
Backups are often bucketed into three categories:
• Full backups – Like filling up an extra tire at the service station, think of this process as pumping all of the data stored on a production system into a backup system for safekeeping. Full backups protect every bit of data from a single server, database, virtual machine (VM), or data source connected to the network. These backups can take many hours, even days, depending on the amount of data being saved. The more modern a data management solution is, the fewer full backups it must perform, and when it does, the faster it goes.
• Incremental backups – Think of incremental backups as adding just a little more air each time you revisit the station—just in case—so you’re always ready to replace your tire. An incremental backup captures only new data since the last full incremental was performed. However, a full backup is required before a backup solution can perform its first incremental backup. Then it can automatically do them based on the last incremental taken.
• Differential backups – Like incremental backups, these add more air but the delta is from the last full backup, not the last incremental. Think of this backup as what’s different from the last time you even filled the tire with air. Again, this can only happen if a full backup has been performed first. Organizations typically establish policies about how much data and when incremental or differential backups should occur.
Cloud computing for Data Availability
Data Science,
Machine Learning,
Deep Learning,
Artificial intelligence,
Statistics for Data Analysis and Data Prediction
Reporting and Visualization Tools for Business Decision Making and Business Prediction
Unix Admin
Micro processer for performance Tuning
Network Administration for Commuting Faster
Languages : SQL, Pl/SQL, Python, R for interacting with Data
ETL /ELT and Data Modeling for better understanding of business operation