by | | dataZap
According to Gartner research, organizations lose approximately $15 million annually due to poor data quality. IBM calculated this value to be $3.1 trillion in the US alone in 2016. This is a staggering number that has occurred due to errors in data input and data quality.
Bad data costs a lot to organizations. Decision-makers, managers, knowledge workers, data scientists, and other professionals have to use it in their day-to-day tasks. And doing so is both time and money-consuming. Due to a pressing deadline and the abundance of faults in the data they require, many people choose to rectify the errors themselves to finish the task. They fail to consider contacting the data originator, outlining their needs, and offering to assist in eradicating root issues. Thus the data errors persist.
The root cause of data errors:
The primary reason for data errors is the typographical and non-conforming of data. Data in many cases are loaded in the form of forms or excel sheets and need people to input the data. People make mistakes, mistype or choose the wrong columns, etc.
The second cause of data inaccuracy is information obfuscation. These occur when people do not give the right information or provide incomplete information to those who enter data.
How to avoid data errors:
A simple solution to avoid such data errors is if you have a system that can validate any data that is input into the system based on set parameters. This way only the right data is added to the system and errors can be corrected immediately. One such solution is Chainsys’s dataZap mass data loader.
dataZap mass data loader:
Chainsys’s dataZap is an integration platform with a mass data loader. It requires no code, no DevOps, and no infrastructure. It comes with 9000+ smart data templates and is certified by both Oracle & SAP.
The dataZap loader process flow:
How Chainsys’s data loader can help you?
To understand how our data loader can be beneficial to your business, we will take the help of examples.
1. Data validation
To stress the importance of data validation let us take the example of Hawaiian Airlines where an employee entered the wrong data of $674,000 for award tickets which had big repercussions on the brand.
To avoid such embarrassing scenarios you can use dataZap loader, which comes with data pre-validation. How is this useful you ask? Before uploading data into the master database or target database, the mass data loader will conduct a pre-validation based on parameters that can be set by you. Only after ensuring the data satisfies the parameters will the data be loaded into the system. This way you will be able to avoid situations that Hawaiian airlines faced.
2. Large uploads in minutes
The second issue that organizations face is the time taken to upload into their system. For this, we are taking our case study where one of our clients used to take 2 weeks to upload 1500 items with 8 computers.
When the client started to use our mass data loader, they found that they were able to upload 1500 items in 4 hrs which previously took them 2 weeks. To clearly understand how the data loader helped the client let’s put this into a table:
*The man hours is calculated as 8 systems * 10 Days * 8 hours a day = 640 man hours
The savings the client got were not just in the form of time but also in the form of resources saved.
3. No need for additional infrastructure
Continuing from the previous example our client had to use their infrastructure to upload data. But with our data loader, you only need 1 system, a browser, and an internet connection. Again the cost to the organization is reduced drastically. Also, the data loader is 100% cloud-based and mobile-ready. Data can be loaded from anywhere and anytime.
4. No Code
With many data loaders, you might need a technical person or specialist to upload data as it requires coding. They need to be babysitting the system when the loading is taking place. But with dataZap’s loader, you don’t need anyone available during the process. As it does not involve any coding you can use anyone to upload the data into the system. This way all your specialized resources can be free to work on other activities that benefit your organization.
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
by | | Data Integration, Data Migration, dataZap
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.
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
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
by | | Data Integration, Data Migration, dataZap
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:
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:
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.
by | | dataZense
What is Analytics
Data analytics is the process of examining large and varied data sets to uncover hidden patterns, correlations, and other insights that can be used to inform business decisions. It involves the use of statistical and computational methods, as well as data visualization tools, to make sense of complex data.
The need for Data Lakes and Data Connectors
Today big organizations are straddled with multiple operational ERP systems, by way of acquisitions or mergers, or other means. So to get the overall picture of the organizational performance and to predict (guesstimate) future performance, a consolidated data lake has to be built and dataZense with its connectors/adapters available for multiple ERP Systems becomes more relevant. With data traffic coming from multiple systems traffic cops become essential (Governing the data coming into the lake – Analytical MDM feature of dataZense). The choice for the data lake has also expanded (Microsoft Synapse, data bricks, Delta Lake, Cloudera, Amazon, Snowflake, Mongo DB, Open TSDB, Google Big Query, and others). Now pumping of data into these lakes (data ingestion) is to be done through specialized receiving ports. dataZense has ready-to-use Ingestion adapters.
Improving Data Quality in the Lakes
Within the lake, all the data brought in from various sources is kept initially in a Bronze layer. The data from Bronze is cleaned and transformed in line with the needs of the Business and moved into the Silver layer. From Silver, analytics-ready data is formed in typically data cubes in the Gold layer. Data de-duping, standardization, and some enrichment also happen between Silver and Gold.
Visualization
dataZense provides dashboards most commonly required by CEOs, CFOs, COOs, CISOs, Shop Floor Planners, etc. Several algorithms are available in dataZense to analyse the data. The crux is to find the right analysis method for the objective, for which we set out to collect data. Sometimes we might use it to find a best-fit line, curve, or graph to best describe the spread of data collected. Other times we may resort to “Machine Learning” techniques or algorithms to answer futuristic questions or group (classify, cluster) the data. The dashboards and reports can be distributed within the organization.
Access Control
Now access to the dashboards, reports, and in general the Gold Layer has to be restricted based on the role of the Business User and geographical location within the organization of the Business User. The access controls are well managed from within dataZense. It has the capability to integrate the Analytics System with popular Identity Management Systems such as Oracle’s OIM (Oracle Identity Management) and Okta. Identity Management Systems can provision access information to the Analytics System.
The Gold layer data can be scrambled or masked based on the critical and sensitive nature of the column of data.
Unstructured data
When we are done doing something, the next thing is ready for consideration in the fast-paced Information Technology world. People today want to rein in unstructured data (e-mail, PDF, excel, word, social media, etc.). Are you wondering how Excel could be unstructured? Yes, unstructured, if people put multiple tables of data in the same sheet, horizontally and vertically. dataZense crawlers get tabular data from Word, PDF, Excel, and e-mail and get them over to the data lake. OCR technology is put to use, where needed.
Meta data
So far it has been data, data, and data. What about metadata (Definition, meaning, and interpretation details for data)? We lose metadata information when systems get old and concerned employees to retire (loss of tribal knowledge). We lose metadata information when there is a rapid acquisition of a company and its systems and no proper transfer of information happens (or if many of the acquired entity employees are fired).
Data Catalog
Data Cataloging is an effort where an organization goes about meticulously collecting and documenting usable data stores lying in various legacy and other systems and filling in missing metadata. If done manually it is a very tedious and time-consuming process. dataZense offers crawlers to analyze (examine) data in columns and see what their nature is, and document the same in a Catalog. Built-in workflow allows many data experts to collaborate and provide/refine metadata. The Catalog would be a living reference document, which would mean constant updating by the parties responsible for it. The Catalog can be used by business analysts and data scientists to know the availability of data across the organization and use the data in Analytics and Visualization.
The data catalog also profiles intelligently and arrives at possible relationships among the columns considered for metadata enhancements. This allows us to create a first cut Entity Relationship (ER) diagram.
Data Lineage
The Data Lineage function of dataZense allows you to track the origin and movement of data throughout the organization. You can see where your data came from, how it has been transformed, and where it has been used. This is especially important for compliance and regulatory purposes.
dataZense Advantage
- Ready connectors/extract adapters from one of the ERPs such as Oracle E-Business Suite, SAP ECC, SAP S/4HANA, Oracle Cloud Applications, Microsoft Dynamics, JDEdwards, Peoplesoft, and others.
- Pre-defined cubes (financial, manufacturing, HR, and other areas) lead to commonly needed dashboards and reports for company executives to make meaningful business decisions.
- Economical Enterprise Data Management (EDM)
- Build and deploy data lakes in platforms of your choice: Microsoft, Amazon, Oracle, Google, Snowflake, databricks, in-house servers, and others
- Data Quality measures
by | | dataZap, dataZen, dataZense, Smart App Builder, Smart BOTS, Smart Data Platform
Computers have been around for a long time, but the general public still doesn’t fully understand how they work. Because of that confusion, there are often many questions surrounding companies that offer computer products and services, especially when those products and services are amorphous. Read on to learn what a software product company like Chain-Sys is.
Software vs. Hardware
The first (and most important) thing to understand is the difference between software and hardware. It’s in this distinction that a lot of confusion around the nature of software comes from. You may think about hardware stores when you hear this term—in that case, hardware refers to things like nails, screws, and cabinet fixtures.
In this case, however, hardware refers to all the physical components required for a computer. This includes the RAM sticks, CPU, video card, hard drive, and more. On the other hand, software is the programs and processes that tell those pieces of hardware what to do. Your web browser, for instance, is a piece of software on your device.
Software: Product or Service?
With that said, many people aren’t sure whether companies that offer software provide a product or a service. That discrepancy is understandable, as products are traditionally known to be physical goods. We believe the best way to look at it is that software companies provide products and services. The design and upkeep of software is the service, while the software itself is a product (albeit a digital one).
Software Company Services
In addition to developing and maintaining software, many software product companies also offer IT services so that you can ask questions about the software. Some software companies may also provide services or products to assist with cloud data management or other processes—it depends on the company.
Now that you know what a software product company like Chain-Sys is, we hope you better understand what we do. If you have any remaining questions, we’re always happy to talk. Contact our team today!
