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 Outdated data systems cause bottlenecks and can lead to countless missed opportunities.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.

3 Oracle Data Migration Mistakes To Avoid

3 Oracle Data Migration Mistakes To Avoid

Data migration is a necessary part of any company’s life if they want to grow their business. We often see businesses realizing that their current database doesn’t have the structure and technology to support them for years in the future, so they switch to a new system like Oracle. Read on to learn three Oracle data migration mistakes to avoid.

Underestimating the Necessary Changes

A new database means a lot of changes. Even though there are some similarities across databases, you can’t avoid organizational and procedural differences. To hit the ground running with your new database, you must devote time to understanding how things will be different. Before beginning the migration, you should consider how management processes and support documentation need to change.

Not Enough Training

Just as you must consider changes from a managerial standpoint, you must also consider the differences for your employees. It will take time for your administrators to learn the ins and outs of the new platform, and they’ll need your support. Allow plenty of time for your administrators to become comfortable with new tools, commands, and utilities.

Choosing Big Bang Over Trickle Migration

The two main types of data migration are big bang and trickle migration. While each has some benefits, big bang migration has significant downsides. Essentially, big bang migration involves getting your whole migration process out of the way in one fell swoop. That may sound ideal, but it can leave you with a lot of problems with your data.

Trickle migration allows you to take things slowly, moving one system at a time. With this method, your Oracle data migration proceeds so that you’re able to correct any issues between batches of migration, leading to a more successful overall transition.

Now that you know these three Oracle data migration mistakes to avoid, set yourself up for a successful migration and enjoy your new database!

What You Need to Know About Smart Data Platforms

What You Need to Know About Smart Data Platforms

More and more businesses are making the transition to smart data, and it’s no wonder why. With smart data, companies of all sizes can have greater control over their business and target the right customers with their products and services. Read on to discover what you need to know about smart data platforms to take your company to the next level.
A Brief History of Smart Data

Data has always been at the heart of a business’s success, whether you look back to the limited demographic information available in the 1940s or the plethora of information we have at our fingertips now. The more a company can leverage data, the better that company will perform. Throughout the 2010s, startups sought to change the way we look at data with the help of artificial intelligence.

The thinking was simple: what if machines could scour billions of terabytes of information to help businesses make logical conclusions about who could benefit from their products and services? Without the help of AI, humans would have no hope of fully leveraging all the data at their disposal.

AI and the Human Element

When you hear the words “artificial intelligence,” you may get a little nervous and picture movies like Terminator. However, AI isn’t scary at all and is relatively useless without human help.

One of the best examples of this is AlphaGo, a computer that matches wits with players in the game of Go. Without professionals to play against, AlphaGo would be unable to match the intelligence needed to put up a significant fight. It’s only thanks to expert Go players who play against AlphaGo that it has become a genius-level Go opponent.

With human help, AI can parse terabytes of data with ease and with accuracy. Without humans to lay the groundwork and tell the AI what data implies, AI could not hope to be truly effective. AI learns much like humans do; without a teacher, AI would not correctly analyze data.

Challenges of Smart Data

In the early days of smart data, there were quite a few problems that needed to be overcome. For instance, having a lot of data isn’t the same as having a lot of useful data. When you leave it up to a new AI to determine what data is helpful and what is inconsistent, you’ll run into some issues.

For example, think about gender demographics most of the year, then consider them around Valentine’s Day. Most of the year, men are not buying jewelry, flowers, and chocolates. When Valentine’s Day comes around, the number of men purchasing those items as gifts skyrockets.

A new AI might incorrectly assume that men have suddenly become interested in those items and urge your business to continue marketing to that demographic after Valentine’s Day. It takes the intuition of a human to tell the AI what’s really going on.

On top of that, without dedicated platforms to access and manage smart data, the utility of the data is limited.

The Advent of Smart Data Platforms

It quickly became clear that dedicated smart data platforms are crucial to the success of businesses working with smart data. These new platforms have the capacity to support huge loads of data as well as more complicated data types than older platforms. One of the most necessary advancements is quick insights, which allows businesses to efficiently pivot when new data is analyzed.

Key Terms

There are three essential terms to understand in the smart data platform world: data management, data engineering, and data science. Each process is crucial to the success of a smart data platform.

Data Management

Data management encompasses everything regarding the acquisition, storage, processing, and application of data. For businesses, data management must also consider quality management as well as the security of your information.

Data quality management is one of the tougher aspects of data management, as it has to do with whether your data is “good” or “bad.” There are a few factors that determine whether you have a good or bad dataset, including integrity, timeliness, accuracy, and consistency. Each of these factors must be analyzed so you know whether a particular dataset is worth looking at.

Data Engineering

Data engineers are the framework builders in the world of smart data. Without the right pipelines, raw data can be practically unusable by data scientists. Data engineering is one of the areas where the combination of AI and human wisdom is crucial. Without the right amount of each, the data may not be as effective as it could be.

Data Science

Finally, data science is where all your information is analyzed and interpreted. In a lot of ways, data scientists must be excellent statisticians, as principles like clustering, classification, and comparison are at play in both fields.

Applications of Smart Data

All of that information does you no good unless there are real-world applications for your business. Luckily, there are many ways to use smart data to your advantage.

Industrial companies, for example, use smart data for predictive maintenance. With smart sensors on their machines and devices, smart data can indicate when components are likely to break down. This allows the company to get as much out of a machine as possible, then replace a few parts quickly and get back to work, reducing downtime and increasing efficiency.

Smart data also has benefits in traditional areas. Targeting and customer segmentation are made much simpler with smart data, and it isn’t hard to use a smart data platform to leverage your insights into conversions. AI helps make the customer experience better for your audience, which leads to more sales for you.

Smart Data vs. Big Data

An area where some people get confused is in the difference between smart data and big data. While big data is great for storing vast quantities of data and noticing global trends, there is a ton of data to analyze. Because of the sheer quantity, big data often comes to outdated conclusions.

Smart data through a platform like Oracle enterprise data management, on the other hand, can analyze and interpret data in real-time. This allows companies to pivot quickly and stay on top of the latest trends.

Now that you understand what you need to know about smart data platforms, step up your game and get your products into the right hands.