What You Need to Know About Intelligent Data Migration?

What You Need to Know About Intelligent Data Migration?

by | | Data Migration, dataZap

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.

Compliance

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.

3 Ways to Leverage Data as a Strategic Asset

3 Ways to Leverage Data as a Strategic Asset

by | | Data Migration, dataZap

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

by | | Data Migration, dataZap, Oracle Data Migration

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.

What Is Data Integration and How Does It Work?

What Is Data Integration and How Does It Work?

by | | Data Integration, dataZap

The free exchange and use of information is an essential element of any business that requires data in order to succeed. Unfortunately, many businesses of all shapes and sizes have problems because they use different systems to carry out various processes.

This strategy in itself makes sense—you want to use the best applications for finances, platform building, and sales—but these programs don’t always come in the same box. However, when you pick and choose applications across a business, it creates roadblocks between departments and works against the easy flow of data. Read on to learn about data integration and how it works to solve this problem.

Defining Data Integration

Data integration is the process of taking data from several sources and combining everything into unified datasets. This has uses both operationally and analytically, and it is often the first step in a wider data management process.

The objective of integration is to create a set of consistent data that is usable for everyone within your organization. Once all the data is integrated, you can use it to gain valuable insights and solve problems in new ways.

There is no limitation to which industries can use and benefit from data integration—if your company has data from disparate sources, integration can help you consolidate and solidify your strategy. When you have information from more sources, the value of your data skyrockets.

How Does Data Integration Work?

With data integration, there are data sources and target systems. Integration pulls data from various sources and routes them into your target system, performing simple cleaning processes along the way to prevent duplicate or redundant data.

For this reason, data integration is typically more complicated than simply directing numbers on a spreadsheet to move to a larger spreadsheet. A program must scour the different datasets to ensure you aren’t left with unnecessary numbers or inaccuracies. Who would have thought combining datasets could be so tricky?

Data Integration Solutions

Now that you have an understanding of data integration, let’s take a deeper look at the problems integration works to solve.

Big Data

Big data is just what it sounds like—vast quantities of data. You’ll hear a lot of people say, “the more data, the better.” While that sentiment certainly has a basis in truth—if you have more data about your customers, you can better tailor your products and advertisements to them—it comes with its share of conundrums.

The two issues that surface regarding big data are data volume and data variety. A robust system takes care of the volume problem, but variety is still an issue—enter integration. Integration helps you organize and decipher vast quantities of data, no matter where that data comes from.

Semantics

A massive issue with rudimentary integration, or integration without cleaning and consolidation, is that you’re likely to be left with duplicate data. Even simple integration systems can catch exact duplicates, but what happens when different pieces of data describe the same thing in different ways?

For instance, perhaps one source comes from overseas, where dates are listed as DD/MM/YYYY; meanwhile, another source comes from the United States, where dates are written as MM/DD/YYYY. You don’t need both variations, so integration steps in to clean things up. This process makes it easier to recognize patterns and avoid being bogged down with unnecessary information.

Data Silos

Data silos are a thing of the past that we’re still tripping over today. As with many other data solutions, you can see the good intentions of data silos while also feeling frustrated by the problems they cause. Essentially, data silos refer to data sources stored in specific locations.

Say a company has a Toledo branch and a Tucson branch. Each location has its own unique set of data that the larger company doesn’t have easy access to since the data is stored on-site. Integration—especially cloud data integration—can take those unique data sources and bring them together in a way that your entire business can take advantage of.

Accessibility

Why create more work than you need to? The best strategy is to make something once, then deliver it to as many people as need it. One central data source eliminates redundancy and reduces confusion while also promoting collaboration.

Benefits of Data Integration

Now that you’ve seen all the problems data integration solves, let’s consider some of the integration’s benefits.

Reduced Costs

The more processes you can automate, the less your employees will need to work to complete tasks. This opens up their schedules to complete new and different tasks, which means you can continue to pay your employees the same amount while receiving more deliverables. The longer the human workflow, the more you end up paying.

Efficiency

Building on the previous point, this boosts the efficiency and productivity of employees companywide. Where some workers could only focus on basic, busy work tasks, they now can dive into more complex work. This gets your customers the results they’re looking for while providing more fulfilling work for your employees.

Better Data Quality

When you work with clean data, overall quality increases. It’s easy to struggle through data with redundancies and inaccuracies without really realizing what’s happening until a computer signals otherwise. All incoming information is validated with integration, which means you don’t need to worry about creating unnecessary roadblocks for your employees.

Upgraded Decision Making

No good decisions are made based on a lack of information. With integration, you and your employees will have everything needed to make educated choices for your business. This is why integration coupled with data analytics is the ideal team—the easier your data is to parse, the better your insights will be.

Enhanced Customer Experience

No one wants to wait around to get answers. With integrated data, your customers will receive the information they’re looking for without spending a lot of time doing it.

Now that you know what data integration is and how it works, consider adding data integration to your information pipeline. Whether you have multiple data management systems or a single coherent system, the integration will bring all your information together for a prime view of all the information at work in your business.

6 Signs You Need a Data Catalog for Your Business

6 Signs You Need a Data Catalog for Your Business

by | | Data Integration, dataZap

Most companies nowadays have access to terabytes of information. Depending on your industry, you may be working with even more! What happens when you need to access a specific data point, and you can’t seem to find it? Unfortunately, the most likely outcome is that you miss out on the opportunity to leverage that data to further your company’s success.

That is unless you utilize a data catalog. Read on to discover six signs you need a data catalog for your business.

What Is a Data Catalog?

The simplest way to think of a data catalog is as a library catalog. When you have a specific book that you want to find in the library, you can check the catalog and search for the book’s title, author, genre, or Dewey decimal code to find it. Your company’s data can work in much the same way—instead of searching based on title or author, you might find data based on fields like customer name or location.

So, how does this work? To understand a data catalog, you need to understand metadata. In short, metadata is data about your data. To continue with the library analogy, a book’s actual content would be considered “data,” while information like the title, author, genre, and number of pages are examples of “metadata.”

A great data catalog makes it easy for you to access data, no matter where it comes from. Through the use of metadata, finding what you’re looking for is a simple and painless matter—just like finding out whether the novel you’re looking for is checked out or not.

1. You Have Data Silos

The first sign that you need a data catalog for your business is apparent if you have data silos. Many businesses don’t know exactly what this term means, and therefore don’t understand whether they have a data silo, so we’ll break it down.

A data silo is a repository of data that is isolated from the rest of your organization. Usually, this subset of your data is controlled by a particular department or unit—it’s called a data silo because a grain silo protects grain from the outside world. While this process can indeed provide a small form of protection, it causes more problems than it solves.

Why do data silos exist if they cause problems? When a company is large enough, different units and departments are often forced to operate independently, with slightly varied goals for the organization as a whole. This is especially true when you don’t have a master data management system in place—a way to unify all your data.

Data silos tend to be incompatible with other sources of data, and they also make it difficult for other units or departments to access the data. While sequestering data may make it a little safer from online threats, it also makes it tougher to access internally.

A data catalog (especially when paired with master data management for security) allows you to govern your data more effectively while promoting collaboration and maintaining integrity.

2. It’s Difficult To Find Data Quickly

Perhaps the biggest sign that you need a data catalog is in the length of time it takes you to access your company’s data. When you instruct your analysts to perform a task like generating a report, how quickly does that come back to you? With a data catalog, your employees can find the data they need with a few short keystrokes and have a report in your inbox within a few hours.

Without this tool in your belt, you may receive your reports too late to act on them. So much of the business world requires quick pivots and agility that slow systems can directly affect your bottom line.

3. You Want To Make Better Use of Machine Learning Tools

If you have machine learning and artificial intelligence at your disposal, you’re shooting yourself in the foot by not also making use of a data catalog. That’s because machine learning tools can use your data catalog to provide you with data inventory in a timelier manner. Just as a data catalog helps your employees easily access data, artificial intelligence will benefit in the same way.

4. You’re Looking for More Out of Your Data

Data analytics is a key part of any company’s path to success. However, even the best analysts in the world won’t be able to effectively use your data if they can’t find the information they’re looking for. Data cataloging helps your analysts achieve their full potential, and thereby helps your company reach its newest peak.

5. You Have Unoptimized Departments

When you keep your data in silos, it serves only to help one department at a time. This can lead to certain departments performing well while others fall by the wayside and suffer. Data cataloging, integration, and master data management bring all sorts of datasets under one large roof and allow every employee equal access to data.

Now, every department can make decisions based on data rather than needing to act on intuition alone. While intuition is a crucial aspect of the success of any company, data-driven intuition helps to eliminate risk and helps employees hone their intuitiveness.

6. You Want To Improve Data Governance

While collaboration between your employees is good, it should also be controlled. This is why data silos form in the first place—to keep proprietary data in the right hands. A data catalog creates traceable data lineage, which helps you track the changes and usage of a given piece of data. This way, if someone uses or edits data they aren’t supposed to, the catalog will record that so you can address the issue.

Using Snowflake for Integration

A data catalog comprises data from all types of sources, and Snowflake integration brings that data together while avoiding the common pitfalls of disparate data. Snowflake enhances analytics and also makes use of a caching paradigm to deliver quick results. On top of all that, Snowflake helps you take down silos and provide better access to data across your entire organization.

Now that you have a better understanding of the six signs you need a data catalog for your business, contact Chain-Sys Corporation with any additional questions about data cataloging. Our team is standing by to help!

Advantages of Utilizing Oracle Data Migration

Advantages of Utilizing Oracle Data Migration

by | | Data Migration, dataZap, 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.

Future-Proof

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

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.

Performance

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?

Security

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.