Data Management – A Historical Perspective

Data Management – A Historical Perspective

It is always interesting to predict the future of technology and data in different ways and from different perspectives to make good decisions. We will therefore define here and present solutions on how Chain-Sys Products and Solutions can fit into an organization’s roadmap. But then prediction is a risky proposition! The best I would try to do is to trace the history of data, applications, and technology over the years since 1959, the year I was born. And I truly believe reading history is the best way to understand the present and predict the future to some extent.


Computers were built using vacuum tubes serving as switches in the fifties and occupied huge rooms, and cooling the heat from the tubes was a great engineering effort. You would have heard stories of how algorithms were run on such computers to crack the code used by the German Army during the second world war. You would have come across Turing Machines, named after Alan Turing, in your fundamentals of computer science courses. So, in the beginning, computers were used to perform computations and repetitive iterations to arrive at answers. Now we use computers to talk, store photos, do video conferences, play games, etc., activities that are far trivial for the wonders that a computer can actually perform.

Digital Transformation

In the early sixties a very innovative device or switch was discovered in the Bell Labs of the USA. This switch did not have glass enclosures or heated filaments; it was a transistor. This innovation made mainframe computers smaller and available to many organizations. Routine end of day bank postings were done by these machines instead of manual ledger postings. Data in magnetic tapes were crunched and written to other magnetic tapes and to print out voluminous reports. Payrolls were run this way too. In the seventies FORTRAN was the popular language for scientific programs and COBOL was the language for business programs. During this era, airlines were a glitzy and glamorous industry. They put up mainframes and terminals at various agent premises and enabled booking and ticketing. The mainframe also checked in passengers at airports, and allowed gate verification and flight closing.

In the seventies, Texas Instruments was the first to put several transistors, resistors, and capacitors in a single chip of silicon. That was the birth of the Integrated Circuit (IC). Soon, it was the Large Scale Integrated Circuit (LSI) and VLSI in the late seventies that came into existence. The Apollo 11 mission did not use any Integrated Circuits. All its systems consisted of transistor circuits on printed circuit boards. The late seventies saw the introduction of the microprocessor with its assembly language and mnemonics. The big players were Intel and Motorola with their respective 8080 and 6800 processors. These technological advances in processor technology and in magnetic storage technology led to the more widespread use of mainframes. Then there were minicomputers and microcomputers. The microcomputer was later named Personal Computer (PC). The relational database (RDBMS) was developed for computers during this time and this led to real-time transaction processing for businesses, as against batch processing. Thus, a need for a central database in each enterprise was felt.


In the nineties, Oracle and Sybase competed for the database market. Microsoft joined the fray in the 2000s. Towards the end of the Clinton presidency, the Y2K hype was unleashed. Several software companies including IBM made their money fixing the year 2000 bug primarily in COBOL and other legacy programs. The 2000s saw the rise of outsourcing of business processes, especially call centers and back-office work. A lot of outsourcing went to India, among other countries. Local Area Networks, especially from Novell Netware, became popular. The email and Internet (WAN) came into the picture. Until it was only LAN, data security was not a big issue, except for employee discipline. Though initially the Internet was used to share information similar to brochures to anyone who had access to the internet and to send instant emails, pretty soon it was making the reach of any computer application global. Anybody anywhere in the world could access a business application and perform transactions. The travel agencies didn’t need dedicated lines to various airline’s mainframes anymore. They could access the applications using the internet, which became a common/public data highway. The common communication medium also brought in problems such as hacking, viruses, and threat to data security.


The database, especially the RDBMS, put into effect the concept of having data only one place across the enterprise. The importance thus shifted from computing to data. Master and transaction data started to be collected in large volumes and business processes were streamlined. Governments and enterprises, big and small started taking advantage of the database concept, and applications were developed in thousands. Often the programmers specialized in particular languages doubled up as analysts and organized business processes and data. Mr. Hasso Platner (founder of SAP) was writing MRP and other applications for various organizations on IBM mainframes. He was modifying his base code for each enterprise. Soon he developed a configurable program that could be set up for different organizations and thus, the R/3 ERP system was born. Oracle saw the business opportunity and developed Oracle Applications, later christened E-Business Suite.

The big ERP systems were deployed on-premise in big servers for applications, middleware, and database. Business and technical experts were needed in all major companies. Large amounts of data continued to be collected. Salesforce (Oracle had a big stake in it) made the Software as a Service model (later called Cloud Applications) popular and acceptable in the market. CRM was not considered a Core Application and salespeople purchased enormous amounts of Salesforce subscriptions. Now that the market was primed for Cloud Applications, Oracle introduced Oracle Fusion Cloud Applications. Though it was highly successful, Oracle has extended full support for the E-Business Suite R12 version all the way till 2030.

With all the data that has accumulated since the nineties till date, there was a huge potential for monetizing data asset(s), by selling (using) it externally or internally. The industry name for such monetization is Digital Transformation. Let’s explore Digital Transformation in further sections.


Some of the questions that are commonly associated with Digital Transformation are:

  1. Is Digital Transformation for People or Applications?
  2. Is a more connected world needed for Digital Transformation?
  3. Where and how does data come into play?
  4. What are the basic building blocks for Digital Transformation?
  5. Is it better to upgrade to Modern Applications or to build new ones?

Connected People

Connected Applications

Connected Data


There is a joke making the rounds, which has a good amount of truth in it. Who brought about digital transformation in our Company? You think it is the CIO, CFO, CTO, or CEO. No, it is the Covid19 virus. Yes, the virus brought collaboration among people onto digital platforms such as chat, video chat, shared documents, and drives. Real organizational Digital Transformation demands more than “collaboration of employees”. It demands “Collaboration and Coexistence of all Business Applications”. It is a connected world after all. Portals-based software (State of the art collaboration between multiple companies, people, and application) are excellent for collaboration and eradication of duplicate efforts. A lot of the tedium can be shifted over to the computer. Nowadays portals need not be confined to suppliers, customers, employee HR, etc. Their power can be massively used to improve productivity by providing portals for each business role, one role at a time. These portals would feed the backbone of ERP systems.

Application to application communication (Master Data and/or Transactional Data) in real-time or batch is very much desirable in any enterprise which uses a multitude of best-of-breed applications.

Born Digital versus Transformed

Many businesses were born “Digital”. For example, Amazon, eBay, Netflix, Roku, Google, Salesforce, PayPal, Expedia, Priceline, etc. They do not have an extensive network of employees to provide products or services to their customers. Most of their products and services are delivered over the web and income is realized electronically in return. Amazon started as an online bookseller. But over the years they converted many of their software processes and internal infrastructure management into saleable products. Many other companies existed long before “Digital” was a popular word. For example, Kelloggs, IBM, GE, Comcast, at&t, John Deere, Fiat Chrysler, Shell, Marriott, and many others. At times, the nature of the products and services they sell, do not allow them to jump into Digital Transformation. They can sell a car online, provide a lot of digital services inside the car, etc., but they have to do a lot of collaborative people teamwork to produce. When they use robots to manufacture their cars, they are doing some Digital Transformation. When they bring all their (most of their) Supply Chain Streamlined into a computerized system, they are undertaking the Digital Transformation journey. Moving tasks from the mechanical and human realms to the computer and digital realms, always provided cost savings, efficiency, and more profits. Compare the cost of making a mechanical grandfather clock vs that of a digital clock. Compare the cost of entertaining a group of people in a theater versus throwing bits and bytes at them through the internet and charging them for a digital movie rented on a streaming site. Storing information (books etc.) is cheaper in electronic format than paper. Digital transformation is not always a formula for success. The customers have to be ready for it.

Data-Driven Enterprise

Digital Transformation is essential to participate and win in the Data-Driven Economy. It was also known some time back by the name “API-driven Economy”, aka “Connected and Communicating Applications”. Data-Driven and API Driven, point to several digital applications and web services complementing each other and contributing to the business objectives. That means they are connected together, they talk to each other, and thrive on inputs from other applications. The synergy generated by the careful orchestration of all Business Applications is very useful and powerful. For example GPS and maps-based computer outputs and displays. They’ve made life easy for the general public and improved productivity in the business world. Another example would be monitoring your fleet of trucks across the country or continent.

Somewhere here we have to realize that “Digital” is just a buzzword to make people buy your stock. It is really the applications that are the stars in this transformation. We have been “Digital” since the mainframes of the 1960s.

When we agree to transform our Applications to participate in the “Data-Driven Economy”, we have to make sure the organizational data is clean, that it has a sufficient record of the past within our organizations, and that we are willing to bring additional insights from vast amounts of sentiments expressed by consumers on social media.

Customer Experience

Operational Agility

Culture and Leadership

Workforce Enablement

Digital Technology Integration

Digital Transformation should lead to “Operational Excellence” of the Organization and also “Decision Making Excellence”. Do we go on a boating trip without checking the weather app for rain and wind? We don’t. Then why as a business leader, would I be satisfied with minimal data inputs and hunches and gut feelings to make decisions. I should demand high-quality reports and facts in various dimensions.

Know thy data. Big enterprises have evolved over many years and through many acquisitions and mergers. They end up with hundreds of operational and analytics systems and huge amounts of data spread across. It is good to catalog the data and find it when needed.

Know thy Customer better. By knowing all aspects and different facets of the customer from different angles, we will be able to hold a more meaningful conversation with them and generate sales.

Going Digital

Digital Transformation is not about seeking one great and mighty application or building one, but about having a Digital Platform, which is flexible and allows the reuse of the various components. Analogy: Buying a Mattel Toy Car vs buying a Lego set. With the Lego set, you can build a car, which tomorrow you can reassemble into a “crane” or “clock tower”. ChainSys Smart Data Platform is similar to the Lego set. The pieces connect well amongst themselves and APIs of external ERPs/Enterprise Applications.

Schneider Electric reduced from 150 ERP Systems to 12 ERP Systems.

What is good for one industry may not be good for another. For example, Sentiment Analysis by retail giants, fashion boutiques, and designers can fetch immense returns. A software products company may not be able to leverage it, just by the fact that their business is B2B and not B2C.

Infrastructure and Building Blocks

Some of the ingredients to achieve Digital Transformation have been around with us for a long time. Robust and secure networks on the infrastructure side. Protocols to exchange information via Web Services. It is time we cook up something tasty with the ingredients. Put them together to work for our organizations. Chain-Sys has wrapped 1000s of APIs into Web Services, covering Oracle Cloud Applications, Oracle EBS, SAP ECC, SAP S/4HANA, Salesforce, Microsoft Dynamics, and others. That means you as an IT person can accomplish a lot with drag and drop, no code low code programming.

Moving your hardware and networking infrastructure to the cloud does offer reduced TCO (Total Cost of Ownership) and better network security and frees up your mind to focus on core business issues and problems.


  • Typical Applications Scenario: Best-of-breed ERP systems on Premise, on Cloud, or Hybrid.
  • Top CRM and HRMS Applications on Cloud, Collaboration, and Productivity Applications from Microsoft, Google, etc.
  • In-house legacy systems, our website, social media and online commerce, portals provided by our suppliers and customers, internet sites, and apps we frequently refer to.

Apart from data integrations/data interfacing using templated Web Services from ChainSys, you can also orchestrate BPA (Business Process Automation) using Smart BOTS™. Hey if you find attacking through the backend difficult, attack through the front end. The same idea is used in automated testing.

Digital Transformation

The challenge is how to make these applications interact, with meaningful human oversight or governance.

Digital Transformation

One of the ways to quickly harvest the benefits of Digital Transformation, without much sweat and money, is to upgrade to the new offerings of Applications Vendors, preferably on the cloud. ChainSys has the tools to migrate your setups and data to the Cloud Applications. At the same time be aware that Customizations are going to be difficult and expensive in the Cloud environment. (You can check with ChainSys for some tricks to get Customizations to work for you fast and simply.

Digital Transformation is more than implementing or upgrading to a single great Enterprise Software. You need a flexible and easy-to-use Digital Platform, which can make your dream projects come to fruition fast and economically. Such a platform would allow you to use various low code no code features and reuse the components you build (think Lego building blocks). For example, the data quality you build for MDM should be available come time for data migration.

We just cannot get up and say one day, “Let’s buy all the Digital Transformation Software and Tools from Microsoft or Oracle for that matter.” We will end up just as a test and bug reporting center for those companies. We have got to be selective and integrate them well with the existing infrastructure, technology, and people.

As a software provider, ChainSys offers the following: Ready glue adapters between most enterprise applications, batched or real-time data exchange, governance, data quality Improvement, quality data to data lakes, AI/ML algorithms to predict business outcomes, planning engines, ability to visualize data in pleasing charts and diagrams, BOTs to do regression testing, etc. We provide the test recordings for the popular ERPs and BOTs to do Business Process Automation, involving multiple Applications. Basically, get/read data from one application, and load it into another application without human intervention, maybe with some amount of supervision.

Some companies are “Born Digital” and others achieve “Digital Transformation”. ChainSys’ objective is to bring “Digital Transformation” in a very flexible, effective, and cost-conscious manner to all the hard-working and excellent companies of the world.

Happy transformations to you all.


I’d like you in the audience to predict good stuff for humanity and planet earth in the near future and send them to I will select the top three predictions, share them with all and also offer winning prizes.

Here is my prediction: As the pendulum has swung to the extreme end of globalization, data and applications shall drive the world back towards a more sensible, sensitive to the local environment, and personalized experience. The supply chain will adjust accordingly. Customer Experience (CX) will reign supreme. Technologists and programmers will chase away tedium in the workplace and make it more fun using collaborative portal-based applications.


Ganesan is a postgraduate from the Electrical Engineering department of IIT Chennai with his bachelor’s from the Electronics and Communications Department of AC College of Engineering and Technology. He has extensive experience in VLSI design, Software Systems Design, and Development, Project Management, Marketing, and Business Administration, and Contracts. Currently is the Executive Director of Chain-Sys Corporation, USA. Before his current role with Chain-Sys, he was associated with Unisys Corporation, DSRC, Tata Unisys, and Bharat Electronics. Presented a paper on “Test Patterns” at the First International Conference on VLSI Design held in IIT Chennai (1984). He has traveled widely in the USA, India, Canada, Europe, Singapore, and the Middle East. His other interests are Story Telling, Creative Design, Painting, Swimming, Hiking, Canoeing, and Kayaking. He speaks Tamil, English, Hindi, and a little Telugu and Kannada.

What You Need to Know About Intelligent Data Migration

What You Need to Know About Intelligent Data Migration

Data migration is one of those things—you know that it has to happen, but you never want to do it. Migrations offer up a whole host of problems, from potential downtime to the struggle of learning a new system. As with many headaches in the business world, someone thought to themselves, “There has to be a better way!”

That person created intelligent data migration, and you’re probably going to be very happy they did. Let’s take a look at the old way of doing things and the reasons this new version is far better. Here’s what you need to know about intelligent data migration.

Lifting and Shifting

Data migration hasn’t always had the opportunity to be “intelligent.” The data migration you’re used to probably makes use of the “lift and shift” method, which is exactly what it sounds like. Essentially, your teams take data from one system, pick it up, and move it to the new system. This is obviously a bit reductive, but it provides you with a good idea of what goes on during the migration process.

To dive a little deeper, your teams have pored over your data to find the fat that you can trim and sought to improve organization during the migration. However, there’s only so much that humans can do when it comes to categorizing and sorting petabytes of data.

Big Bang vs. Trickle Migration

We can further break down the “lift and shift” method into two main types of data migration: big bang and trickle migration. With big bang migration, the entire process happens in one go—you push a button, and migration begins. That migration doesn’t stop until you port over all your data to the new system.

The main drawback of big bang migration is that it renders your systems useless during the process—all your computing power goes into migration. Unless you can afford days or weeks of downtime, it’s usually better to choose trickle migration.

Trickle migration, on the other hand, has a “slow and steady wins the race” mentality. Your teams will come up with the optimal order to transfer data to your new system, moving forward one piece at a time. With trickle migration, you don’t need to worry about downtime—your old system is still functional during the shift.

While both of these types of migration do the job, they require a lot of brainpower from your team and are likely to leave you with problems in your new system. This isn’t the fault of your team, but it’s because different systems work differently. You never know when a particular piece of data won’t sit right in a new system.

Fortunately, these problems are annoying but correctable. And, even more fortunately, intelligent data migration can help you avoid these problems altogether.

What Is Intelligent Data Migration?

As with many other “smart” processes, the difference between regular and intelligent data migration is the addition of artificial intelligence. AI will discover your data—it will look for all the different types of data at use in your business.

Artificial intelligence then classifies that information based on how critical it is. The determining factors include both the importance to your company and its importance in the data privacy regulations hierarchy.

The main idea of intelligent data migration is to use insights generated at fast speeds to sort and organize data efficiently. Once the artificial intelligence has delineated where the data is going, you can perform a low-risk migration at the optimal speed.

How Does That Work?

It’s all well and good to say, “Artificial intelligence makes magic happen,” but what is really going on behind the scenes? In a way, the actual action that your AI is taking isn’t any different from what a human would do to organize data. However, AI can do it much faster.

Essentially, the AI looks over metadata to find out what type of document it’s dealing with, how old the document is, the file size, and who has access to the document. Using all this metadata, the AI can determine where the data needs to go—either ported into your new system or left behind if the information is unnecessary.

Why You Should Use Intelligent Data Migration

You know that AI can help you speed through data migration, but why else should you use intelligent migration? We’ve made a list below of all the benefits of incorporating this technology into your strategy.

Reduced Storage Costs

One of the biggest benefits of using these data migration tools is that you can save money on data storage. Intelligent migration will find a ton of redundant information that you can leave behind—and with each piece you leave, you free up more storage space. By the time the AI looks over everything, you may need a lot less storage space than you assumed.

There’s no need to pay a premium to keep obsolete information on hand. Open up your IT budget and breathe easier when you see the bottom line.

Reduced Migration Costs

Data migration isn’t cheap, but when you migrate fewer documents, the process takes less time. In addition to saving storage money, you’ll also be able to make use of your new system sooner. On top of that, many AIs require training before you can use them. Luckily, intelligent migration AI comes pre-trained, so you don’t need to spend any time doing that.

Better Productivity

Once everything is in the new system, your employees will be able to work more efficiently with less unnecessary information clogging up the system. It’s far more difficult to get things done when you need to sift through old files before you can begin.


Proper data storage isn’t only a matter of convenience—there are also state and federal mandates that require you to classify data in a certain way. To avoid fines that come about through human error, let artificial intelligence do all the work!

Now that you understand what you need to know about intelligent data migration, decide whether it’s a tactic you want to employ at your facility the next time a migration needs to happen. There’s nothing better than efficiency, so talk with your teams and figure out if intelligent data migration is right for you.

Data Estate: Building Sophisticated Data Infrastructure Through Modern Technologies

Data Estate: Building Sophisticated Data Infrastructure Through Modern Technologies

Data, pandits say, is now the most valuable resource on the planet. Even more than oil. With the world advancing daily and adopting newer digital technologies with every passing minute, it hardly seems like an exaggeration. Today, data is the most valuable currency a company possesses.

Today’s organizations deal with voluminous data on a daily basis. Whether it’s data generation, storage, or harnessing data to make business decisions, data plays an integral role in multiple operations that are vital to the functioning of these companies. Different teams have access to, handle, and analyze this data on an ongoing basis, making data management a cumbersome task.

What is Data Estate?

Companies are drowning in data coming from heterogeneous sources and struggling to find a solution to structure it all. That’s why a term called Data Estate is trending in the industry nowadays.

Data Estate is nothing but all the data, from all the sources, that a company owns and is usually what needs modernization. It’s simply to build a data infrastructure, through modern technologies to ingest and store all your data with governance and quality protocols in place. This can be developed on-premise or cloud. You can even get the best of both worlds by using a Hybrid approach depending on the business requirements. This helps make organizations proficient in storing, managing, and leveraging your data for analytics including business applications, IoT, departmental data, and more!

How to Get Started:

Before you begin towards building a successful data estate, there are a few key questions that should be answered which will guide you in your journey of implementing an infrastructure.

  1. What is your end goal that you want to achieve?
  2. What are your short term and long term business requirements?
  3. What are your current Business processes and how do they integrate with your current data processes?
  4. Who will have access to the data and which data will these persons have access to?
  5. Would you like to go On-Prem, Cloud or Hybrid? Why?
  6. What will your construction Partners look like?
  7. It is a complex and challenging project. Make a roadmap with smaller tasks to achieve the end goal.

Seems overwhelming? But it’s really not. ChainSys will be able to help you answer all these questions and build the entire infrastructure for you including automation. Our end-to-end data management platform ensures data access in a clean and secure manner while standardizing all data to minimize the risk of data loss, duplication, etc. This ultimately translates into real-time results which harness the true value of your data while saving you money, time, and resources.

How ChainSys Can Help:

With over two decades in the industry, we have helped a plethora of clients from various industries including, energy, aviation, finance, technology, manufacturing, and more! Our data solutions are 360-degree right from the beginning, all the way to the end, some of which include:

  • Migration & Integration
  • Quality, Cleansing & Governance
  • Active Metadata Management
  • Enterprise Data Management
  • Analytics and much more

At ChainSys, our approach is customer-centric. We begin by understanding all the above requirements and build a customized team of experts that are experienced with your industry and uniquely suited to tackle your specific challenges. This team will then dive deep into your business and data processes, and your legacy systems and do all the necessary homework. Following which, we will not only draw out solutions specially designed for you but also build a roadmap to help us achieve your goals together, in a timely fashion. 

If you’re looking to level-up your data management game, get in touch!

To view all the Solutions we offer, click here.


3 Ways to Leverage Data as a Strategic Asset

3 Ways to Leverage Data as a Strategic Asset

No matter where you turn for business advice, you’ll always hear the same thing: find a way to leverage your data. While that may be a great tip, it’s missing an essential part of the equation: how? Consider these three ways to leverage data as a strategic asset.

Connect With Customers

Customers want personalization, and you can use data to give them just that. Tailor advertisements to individuals and determine which of your products is perfect for them. When a customer feels like a company understands them, they’re much more likely to make a purchase.

Make Data-Based Decisions

Data can help make you smarter. Even if you’re the smartest person on the planet, you still have the potential to make mistakes that numbers simply don’t. Utilize those numbers and data analytics to make decisions driven by hard data. That way, you can set up your company to perform well for years to come.

Optimize Your Website

Did you know you can collect data on how people view your website? Demographics are one thing, but you can actually obtain information that tells you exactly what people are doing when they visit your site. For example, you can see which images people look at the longest, which links they click on, and on which page they decide to close your website.

Using that information, you can start to build a better website. Utilize the pictures your viewers seem to prefer, and figure out why everyone decides to leave your site after reading your “About” page. With an optimized website, you’ll find yourself enjoying more conversions than ever before.

If you’re not sure how to gain any of these benefits, you may want to consider implementing Microsoft data migration to bring your systems to the next level.

Now that you know these three ways to leverage data as a strategic asset, make sure your systems are working for you and not against you. The right master data management system will actively help your business leverage data better; consider a data migration if you find yourself fighting against your current software.

4 Preparation Tips When Migrating to an Oracle Cloud System

4 Preparation Tips When Migrating to an Oracle Cloud System

Data migration is a common tactic for companies looking to move up in the world. Outdated data systems cause bottlenecks and can lead to countless missed opportunities. When you upgrade to an Oracle Cloud system, you create a more mobile and effective business. Read on to learn four preparation tips when migrating to an Oracle Cloud system.

Create a Plan

A migration strategy is the first thing you need. While you might think migrating data is as simple as directing data in your old system toward your new one, there’s a lot more to it. In fact, a full transition can take several months! You need to consider everything from migration type (big bang or trickle migration) to data backups and reporting.

Identify Key Performance Indicators

During the planning process, make sure to establish Key Performance Indicators or KPIs. These describe your goals for the migration. What does success look like? You’ll want to think about transition time, the overall cost of migration, and how your applications perform, as well as any other factors you deem important.

Get Your Data Ready

Data from various sources tend to contradict, from minuscule discrepancies to significant differences. Before you start your migration, make sure the data is ready to travel to its new home. Ensure consistent data to avoid inaccuracies and redundancies in the new system.

Train Users

Implementing Oracle EBS data migration takes a while—plenty of time to get your team trained up on how to use the new system. During the long migration, make sure your employees learn the Oracle Cloud system so that you don’t miss a beat when the new system is ready to go. There’s no need for your business to take a backseat during the transition—keep productivity up!

Now that you know these four preparation tips when migrating to an Oracle Cloud system, set yourself up for success! If you follow these suggestions, you’ll be poised to tackle the new system with aplomb.

Advantages of Utilizing Oracle Data Migration

Advantages of Utilizing Oracle Data Migration

Bringing your business into the cloud is the same as bringing your business into the future. When working as heavily with data as companies do these days, there’s no reason to leave everything in physical data centers—all that does is unnecessarily inflate costs. Read on to learn the advantages of utilizing Oracle data migration.


When your company can’t tackle a new project because your hardware is holding you back, that’s a very frustrating feeling. Fortunately, you won’t have to worry about that with the Oracle Cloud. This is a system that shifts and grows with you and stay up to date no matter what.


Agility is a buzzword we’ve all heard before, but it’s a critical one for the business world. Can your company quickly respond to trends and changing conditions? If yes, you’re likely to find success in this fast-paced world. If no, you may have to move some things around to stay relevant. When you bring your data into the Oracle cloud, it’s easy to perform quick analytics tasks and pounce on new opportunities.


When applications run through physical servers and CPUs, you’re constrained to the hardware you have. Those constraints are gone with the cloud, which affords you much more flexibility and reliability. You don’t need to worry about systems crashing or taking forever to compute—and when you can access higher performance at lower costs, why not do it?


When you migrate your data to the cloud using Oracle data solutions, you’re taking a concrete step to put up walls around your proprietary information. Oracle has cutting-edge data encryption, which means that you and your users can feel safe putting data into your system. Oracle’s system also allows you greater control over security than other programs, which helps to maintain visibility company-wide.

Now that you understand these advantages of utilizing Oracle data migration, bring your business into the Oracle Cloud and get ready for all the benefits that come with it! One simple change can transform your company’s future—make that change today.