Data Management Services Help Your Business

Data Management Services Help Your Business

How Data Management Services Can Help Your Business?

To run an organization successfully, every business needs data. Massive amounts of data of various kinds are being gathered and stored by businesses, but managing and analyzing this data could be difficult. In this case, data management services can be useful and also considered to be a crucial component of corporate operations in the current digital era. We’ll explore more about what data management services are and ChainSys, a data management firm, offers a variety of data management services that help your business in this blog.

What are data management services?

Data management services refer to a collection of procedures and tools for gathering, archiving, organizing, securing, and maintaining data across the course of its lifecycle. It includes a broad variety of operations, such as data integration, data governance, data migration, data quality management, data analytics, data security, and data storage.

Let’s take a closer look at various data management services:

Data Management Services

  • Data Integration:

The process of merging data from various sources into a single, unified view is known as data integration. dataZap, Chainsys’s integration platform helps you integrate and transform data from any source. No coding is required and high volume integrations of up to 1 million records can be done in an hour. It also keeps data clean by validating & cleansing during data integration.

  • Data Governance:

Data governance refers to the set of policies, procedures, and standards that guide the management of data assets. It manages the actions and processes people must follow. With dataZen it is an easy-to-build workflow with data governance tools and it monitors the creation of data dictionaries to make sure everyone has an understanding of the data, to identify, it collaborates with various departments across the organization to confirm that the data is used  consistently across the organization.

  • Data Migration:

Transferring existing historical data to new storagee, a system, or a file format is known as data migration. While the process may sound quite simple, it requires a change in storage, a database, or an application, but ChainSys approaches complex data migration to various ERP and Enterprise Application needs with simplicity and robustness with its ready-to-use 7000+ Data Adapters for Data Extraction, Data Loading, and Data Mappings from Source to target applications.

  • Data Quality Management:

Data quality management (DQM), a business strategy, aims to enhance the data quality metrics that are most important to an enterprise company, by bringing together the necessary people, procedures, and technologies. ChainSys’s cloud-based dataZen data quality management platform enables businesses to identify inconsistent and erroneous data across their applications and provides you with data cleansing tools as well as the ability to de-duplicate data.

  • Data Analytics:

Data analytics refers to a collection of quantitative and qualitative methods for extracting insights from data. With dataZense a holistic data and analytics platform provides rapid results by following the most efficient processes to ensure governance and quality to bring forth a single source of truth for information at all times, thus driving sustainable decision-making across businesses.

  • Data Security:

Data security is the process of defending your information against unauthorized access or usage that can expose, delete, or corrupt that information. Using dataZense for Data Security, you can avoid internal and external data breaches and have simple sensitive data management by providing comprehensive data security management, data masking, and data scrambling solutions for many applications.

In what ways the above data management services can benefit your business?

Data Management Services

To conclude, data management services can help businesses in many ways, from improving decision-making to reducing costs and gaining a competitive advantage. Whether it’s a small business or a large enterprise struggling to manage data, ChainSys smart data platform would be a great investment as it helps in maximizing the value of data.

dataZap – How it can optimize your business operations

dataZap – How it can optimize your business operations

According to Gartner research, organizations lose approximately $15 million on average per year due to poor data quality. Staying ahead in today’s environment requires access to reliable data at a moment’s notice. Smart businesses invest the time and resources needed for effective data integration, which is an essential part of creating successful analytics programs that drive overall success. Data integration solutions aid in transferring data from the source to the destination, accelerating and streamlining the process.

Finding the right people to complete projects involving data integration can be expensive and challenging. Using many coding languages and frameworks adds another level of complexity. Upskilling resources to get data into and out of source systems becomes more difficult.

Moreover, several businesses manage multiple data marts across various cloud ecosystems. It is difficult to swiftly and simply integrate data across platforms. The solution must integrate all the data, which will make it possible to switch over smoothly to an enterprise-grade platform. Additionally, it gives you access to all the data required for efficient analytics.

Maintenance tasks need to be carried out throughout the data lifetime to keep your data integration current. This entails tracking how your data integration tools are being used, leveraging outside schedulers to conduct your processes, configuring new users, and carrying out upgrades.

All this and more can be done with a data loader. Chainsys’s dataZap is a data migration and integration platform. It requires no code, no DevOps, and no infrastructure. It comes with 9000+ smart data templates and is certified by both Oracle & SAP.

5 ways dataZap can help optimize operations
Listed below are some of the ways that our mass data loader can help your organization reduce maintenance and operational costs.

dataZap-maintenance-and-operational-costs

1. Pay for what you use
You will only have to pay for how much data has been used. You can upload as much data as you need into your data warehouse. But for any integration to be successful you will need to keep track of who is using the data loader and the jobs being executed. dataZap comes with a dashboard that will give you an in-depth analysis of who is using the application and the amount of data that is being processed.

How you benefit – Any project will involve multiple teams and people such as developers, data engineers, analysts, and business teams. With so many people involved you might have to get a subscription for them all. But with the dashboard, you can find out who is effectively using the tool and restrict access to them. This way you can cut down on the costs of subscriptions where the tool is not used.

2. Data validation and reconciliation

Data validation and reconciliation
Without quality data, any decision that is made cannot be 100% correct. When integrating or updating data, care must be taken to ensure the data is correct and without errors. If done manually human errors are prone to happen. All this can be avoided with the dataZap which comes with prevalidation and data reconciliation.

How you benefit – Any business decisions that the top management makes will have company-wide repercussions. Having clean data uploaded the first time ensures that any analytics or decisions taken will be accurate and make it effective.

3. Visualization and monitoring
To measure the success of any tool you require actionable information. Chainsys’s dataZap has a reporting engine that generates reports on the various adapters’ execution and produces dashboards to understand the actions taken and to be taken. The information in this section will be organized into job name, status, rows processed, start time, and end time. Click on any job to view the work’s attributes, outcomes, and information about the subtask. You will get an error notice if the job fails. On the same page, you may download logs. Users can view the log details without needing additional access to other environments.

How you benefit – In case you have multiple data points that need to be updated in your data mart, you can pause any analytical operations till the data are successfully uploaded. The dashboard will give a notification when all the jobs are completed without the need to individually contact the teams at the site for a status update. Once the data is loaded successfully the analytics program can be initiated automatically.

4. Task scheduling
dataZap data provides the capability to schedule tasks without any external simulators. By scheduling known or repetitive tasks you can free up resources internally and focus on other business priorities.

How you benefit – Following up on our previous example, suppose an analytics operation requires data from various sources and the sources are in different time zones, it is not possible to get the information at the same time. The analytics operation can be scheduled to run when data from all the regions are uploaded successfully and in any time zone. Due to this requirement, the data is regularly loaded and the report is readily available when required.

5. Working in shared environments
Many organizations have shared data and data siloed in multiple environments. Bringing them together into one location is difficult and in many cases costly. dataZap allows working on multiple environments at the same time.

How you benefit – Consider your company is acquiring another company and you want to upload large amounts of data from Salesforce to your system which is SAP. For an analytics need now they also merge multiple data warehouses. Now you can upload all the data into one data warehouse by inviting the other analysts to the dataZap. They can use existing tasks or build their own. This will help reduce costs as you will not need to create new pipelines or go for more third-party integrations.

Get started with dataZap data loader
Are you interested in our data loader into your data integration strategy to help optimize your maintenance and operational costs? Get on a call with our experts for a live demo and how we can specifically help your organization.

Request a demo

Or you can go through our resources to understand more about dataZap and mass data loader
Mass data loader
dataZap Architecture

Oracle Cloud Infrastructure Migration: A Comprehensive Guide

Oracle Cloud Infrastructure Migration: A Comprehensive Guide

Migrating to the cloud can be a daunting task, especially if you are unsure of how to do it. Oracle Cloud Infrastructure (OCI) provides a suite of tools and services to help you migrate your workload seamlessly and efficiently. In this guide, we will take a deep dive into OCI migration and provide you with a comprehensive guide to successfully migrate to the Oracle Cloud Infrastructure.

Benefits of Oracle Cloud Infrastructure Migration

There are many benefits to migrating your organization’s IT infrastructure to Oracle Cloud Infrastructure. Here are a few:

Oracle Cloud Infrastructure Migration

Increased Efficiency: Moving to the cloud infrastructure eliminates the need for investing in hardware and software, leading to cost savings. This makes it easier for organizations to focus on their core business activities. With a cloud-based infrastructure, scaling up or down is also quick and easy.

Better Security: Security is a top priority for Oracle Cloud Infrastructure. With its advanced security features, organizations can be assured that their data is secure. Additionally, Oracle offers data encryption, DDoS protection, and identity and access management to further strengthen the security of the infrastructure.

High Availability: Oracle Cloud Infrastructure is designed for high availability, ensuring that mission-critical applications and services are always available. The infrastructure provides automated backup and recovery options to ensure that organizations can continue operations even in the event of a disaster.

Reduced Downtime: Downtime can be costly for any organization. With Oracle Cloud Infrastructure, organizations can reduce downtime by leveraging its automated backup and recovery options. Additionally, with its built-in redundancy and failover capabilities, the infrastructure ensures that services are always available.

Improved Performance: Oracle Cloud Infrastructure is designed to provide high performance and low latency. Organizations can expect fast and reliable access to their applications and data, leading to improved productivity and customer satisfaction.

Enhanced Flexibility: With Oracle Cloud Infrastructure, organizations can easily scale up or down as their needs change. This flexibility allows organizations to quickly adapt to changing business requirements and respond to market demands.

Types of OCI Migrations
OCI offers two types of migration:

Lift and Shift Migration: In this type of migration, you move your workload from your on-premises environment to OCI without making any changes to your workload.

Application Migration: In this type of migration, you optimize your workload for the cloud by making necessary changes to your application architecture.

OCI Migration Steps
Here are the steps to follow for a successful OCI migration:

Oracle Cloud Infrastructure Migration

Step 1: Discovery and Planning
The first step in OCI migration is to discover and plan. This involves understanding your workload, identifying dependencies, and planning the migration. You can use Oracle’s discovery tool to scan your environment and identify the workload that needs to be migrated.

Step 2: Network Setup
The next step is to set up your network. This involves setting up your Virtual Cloud Network (VCN), subnets, security rules, and connectivity options. You can use Oracle’s Networking service to set up your network.

Step 3: Compute Setup
The third step is to set up your compute resources. This involves creating your Compute instances, attaching block volumes, and setting up your load balancers. You can use Oracle’s Compute service to set up your compute resources.

Step 4: Data Migration
The fourth step is to migrate your data. This involves copying your data from your on-premises environment to OCI. You can use Oracle’s Data Transfer service or other third-party tools to migrate your data.

Step 5: Application Migration
The fifth step is to optimize your application for the cloud. This involves making necessary changes to your application architecture to take advantage of OCI services. You can use Oracle’s Application Migration service to automate the application migration process.

Step 6: Testing
The sixth step is to test your workload in the OCI environment. This involves testing your application, performance, and security in the cloud environment.

Step 7: Cut Over
The final step is to cut over to the OCI environment. This involves switching your traffic from your on-premises environment to the OCI environment. You can use Oracle’s Load Balancer service to manage your traffic.

OCI Migration Best Practices
Here are some best practices to follow for a successful OCI migration:

● Start with a small workload to gain experience with OCI.
● Create a detailed migration plan and follow it rigorously.
● Optimize your workload for the cloud by taking advantage of OCI services.
● Test your workload in the OCI environment before cutting over.
● Monitor your workload in the OCI environment to ensure optimal performance and security.

Conclusion
In conclusion, migrating to Oracle Cloud Infrastructure can bring numerous benefits to organizations. It can help to increase efficiency, improve security, provide high availability, reduce downtime, improve performance, and enhance flexibility. With its advanced features and capabilities, Oracle Cloud Infrastructure is a solid choice for organizations looking to modernize their IT infrastructure and stay competitive in today’s fast-paced business environment.

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.

data-management

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.

data-management

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.

data-management

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.

DIGITAL TRANSFORMATION

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

Collaboration

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.

Applications

  • 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.

The FUTURE:

I’d like you in the audience to predict good stuff for humanity and planet earth in the near future and send them to prediction@chainsys.com. 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.

AUTHOR BIOGRAPHY:

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.

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.

Smart-data-platform

What Is Data Integration and How Does It Work?

What Is Data Integration and How Does It Work?

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.