Solutions and Tools for Managing Unstructured Data

Solutions and Tools for Managing Unstructured Data

by | | Data Integration, Data Migration, dataZap, dataZen, dataZense

In this Data-driven business world, Data is like gold whether it is in Structured form or Unstructured form. Structured data is information that has a set format and is simple to obtain and comprehend. Unstructured Data is the type of data that does not fit into a predefined or traditional format. Unstructured data includes everything from emails, social media posts, and customer feedback to images, videos, and audio recordings generated by individuals/customers. Almost 80% of businesses believe that between 50% and 90% of their data is unstructured, however, this does not indicate that the data is useless. Unstructured data contains valuable insights that can help organizations make better decisions, improve customer satisfaction, drive innovation, and gain a competitive advantage.

Let’s understand it by taking an example – Social media help organizations to understand the trends, customers’ reviews, and their emotions with a brand, and their satisfaction level while analyzing sensor data can help brands to optimize their business strategies.

If you want to make your unstructured data ready to use, Data Management is the only choice. Managing Unstructured Data is not an easy task because it generates a large volume of data that is difficult to store, manage, and analyze. Security measures are also required to protect the confidential information of individuals. Unstructured data can be of varying quality and may contain errors or inconsistencies. For example, text data may contain spelling errors or typos, while images may be of varying quality or resolution.

Managing unstructured data can be a challenging task, but there are solutions and tools available to help:

Managing unstructured data

Data Extraction can be Aided by Data Mining Tools: Data Mining tools are successful to extract valuable information from Unstructured data and you can use that information later on. These tools are useful to analyze customer feedback, social media posts, and emails to identify patterns and trends. On the basis of customer buying behavior, patterns, and trends, these tools can help you to predict future demands/outcomes. Unstructured data analysis can assist you in focusing on the areas that require improvement and helping to make the appropriate judgments.

Data Storage in the Cloud: Large amounts of unstructured data can be managed by enterprises using a scalable and affordable option called cloud storage. To store and manage unstructured data, there are numerous incredible Cloud storage options available, like Amazon S3, Microsoft Azure Blob Storage, and Google Cloud Storage. Yet, due to scale and security concerns, several businesses also favor storing their data on-site. Ultimately, It relies on the needs of businesses.

Data Visualization Tools: Unstructured data can be difficult to work with, but visualization tools can help simplify complex data by presenting it in a more understandable format. A graphical display of data can captivate the viewer and provide a clear image of insights that can aid in more effective decision-making.

Data Lakes: Data Lakes are cost-effective solutions to store, manage and analyze a large amount of Unstructured Data in its original format. Data lakes enable data to be stored and accessed without having to be transformed into a specific structure or format, making it simple to integrate with existing data.

Text Analytics Tools: Unstructured Data comes in different formats such as images, videos, audio, and text. Text analytics tools are aimed at analyzing textual data such as emails, social media posts, and customer feedback. The primary goal of these tools is to extract useful information from text format. Natural language processing (NLP) is used in these tools to extract insights and trends from unstructured data.

There are various incredible tools with their own USP that you can use to manage Unstructured Data:

MonkeyLearn – MonkeyLearn is a Text Analysis platform with Machine Learning to automate business workflows and save hours of manual data processing.

MongoDB – MongoDB is a next-generation database that helps businesses transform their industries by harnessing the power of data.

Apache Spark – Apache Spark is an open-source unified analytics engine for large-scale data processing. This multi-language engine is for executing data engineering, data science, and machine learning on single-node machines or clusters.

Hadoop – Hadoop is an open-source software framework that facilitates the distributed storage of data across clusters of computers.

Amazon S3 – Amazon Simple Storage Service (Amazon S3) is an object storage service offering industry-leading scalability, data availability, security, and performance.

Managed data is easy to access and use, you can find out the right information at the right time and it leads you to deliver better results. Unstructured Data Management tools help you to monitor your customers’ every move and provide real-time insights. You can track your customer’s preferences, understand their needs, and relationships with your brands, and deliver better services to them.

Data Management Services Help Your Business

Data Management Services Help Your Business

by | | Data Integration, Data Migration, dataZap, dataZen, dataZense, Master Data Management

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.

Chain-Sys: What Is a Software Product Company?

Chain-Sys: What Is a Software Product Company?

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!

What Is Master Data Management and Why Is It Important?

What Is Master Data Management and Why Is It Important?

by | | dataZen, Master Data Management

Working with data is unavoidable for companies that want to stay relevant. However, just “working with data” isn’t always enough to cause you to stand out from the pack. To set yourself apart, you need to work with data more efficiently and effectively than your competitors. That’s where master data management comes in. But what is master data management, and why is it important?

You’ve come to the right place. Read on to discover what you need to know about master data management.

Master Data Management: Explained

To understand the management part of master data, the first step is understanding master data. When we break it down to its simplest definition, master data refers to the most vital instances of data in your enterprise—all of the information that’s required to conduct business.

Of course, this can be further divided into a few different domains. For instance, your customers, products, and locations are all key elements of master data. Without any one of those elements, your company could not survive. You should also consider a subset of “other” factors, like warranties and contracts. All these unique elements comprise your master data.

Master data management, then, refers to how your business handles all that information. Now, things may get a bit more confusing. Master data management technology, often called MDM, allows you to perform tasks with data management in mind. Master data management as a discipline is more conceptual—it gives you principles that will help you govern your data successfully.

Reduced Workload

The collection and maintenance of master data is a full-time job—one that you should leave to a dedicated master data management system. Without one, you’re expecting every department to spend time managing their own data alongside their regular job functions.

As soon as you remove data management from the workload, all your departments will find it easier to complete their work on time (or even early). A master data management system allows you to collect each piece of data simultaneously rather than having each department collect and utilize the data separately.

Over time, this makes your business quicker and more efficient, which saves you money while getting the reports you need on time.

Higher Data Quality

When separate departments are responsible for maintaining their data, you’re bound to run into snags along the way. Without a way to manage master data, departments will grow away from each other rather than together, leading to problems with collaboration that only increase as you go.

Master data management allows everyone to access a single source of data, which means your information will not dilute as time goes on.

Avoids Data Duplication

One aspect of data quality that is often overlooked is duplicate data. When you don’t have a system that can look for and detect duplicate data, you may find yourself with information that gums up the works. With a decentralized data application, you’re more likely to run into redundancy that can take up your time and cause errors throughout the process.

Duplicate data becomes a significant hurdle when you acquire information from customers. Slight changes in your questionnaires over the years may cause customers to enter their information multiple times in slightly different ways. For instance, you may have records that refer to a customer living at 1340 Delta Avenue and another record that lists them at 1340 Delta.

You don’t need both these instances, and it may cause a less intelligent program to assume you have one more customer than you do. When this issue occurs across hundreds or thousands of customers, you’re left with analytics that doesn’t accurately reflect your customer base.

With an MDM solution, you won’t need to worry about duplicate data. Your MDM will scour through data to find repeat instances and remove them, increasing your efficiency.

Reduced Time-to-Market

Setting up new systems is always a headache, right? It doesn’t need to be with a dedicated MDM. Connecting a new system to your primary MDM system instantly populates the new application with all the data it needs to hit the ground running.

Upgraded Decision Making

When all your data is in one place, your teams can make decisions with a clearer picture. Without a master data management system, you can think of this process like putting together a puzzle without the box—you may have all the pieces, but you don’t know the picture you’re trying to create!

As new data comes in, it instantly updates the information across your company. This leads every team to make decisions with all the latest information they need to propel them toward success.

Compliance and Governance

Regarding benefits, “compliance and governance” may not be the most attractive words, but they are some of the most essential words should you want your business to stay strong for years to come. While it may sound more appealing to increase efficiency and reduce your workload (which MDM can also do), you can’t maintain a company without staying in compliance and structuring your systems with governance.

This structure allows you to restrict access to data, giving your employees the information they need to do their jobs effectively while preventing them from accessing data they shouldn’t. All interactions with data are also cataloged, which means it’s easy to trace problems back to their source so you can correct them.

Reduced Security Risk

Extrapolating on this further, MDM tools also assist you in tightening your security. Breaches are extremely serious; if they happen, you can quickly see where the problem began so you can address it.

In all, a business equipped with the right master data management tools stands to work more efficiently and safely than other companies in the game.

Now that you know what master data management is and why it’s important, start the next chapter of your business’s story and begin working in an MDM system. You won’t believe how adding an MDM system to your business pipeline can completely transform how you work!

What Is Data Cleansing and Why Does It Matter?

What Is Data Cleansing and Why Does It Matter?

by | | dataZen

What Is Data Cleansing and Why Does It Matter?

Not everyone knows that data can be dirty. Dirty data poses a myriad of problems to businesses all over the world, so they want to know how to clean the data up. As time goes on, data gets dirtier, making the cleaning process more and more challenging. But what is data cleansing, and why does it matter? Read on to find out.

Cleaning Data

So, what do we mean when we talk about “dirty data?” Dirty data is not information about waste management. Instead, this phenomenon refers to data that’s incomplete, duplicated, or inaccurate. Dirty data doesn’t just spring into existence, though—it comes from somewhere. Typically, dirty data originates due to poor communication, user error, or even a bad data strategy.

Whether you know you have dirty data or you just want to play it safe (which is never a bad idea), data cleansing is your go-to solution. Data cleansing is a process that works to filter out the dirty data and clean it up. Essentially, the cleansing process removes or resolves every instance of incomplete, duplicated, or inaccurate data.

Data Quality

All the data in the world does no good if you’re not working with quality data. Dirty data can waste your time and even cost you serious money. When you work with high-quality data, you don’t need to worry about throwing money at a problem that doesn’t exist except within spreadsheets. That’s what low-quality data can do—tell lies through statistics.

Importance of Data Cleansing

Cleansing your data catalog is important because dirty data is a recipe for misinformation. You may not know the truth about your organization’s processes without a little data cleansing to help you! With master data management, you can clean your data easily and efficiently.

Now that you know what data cleansing is and why it matters, make sure you give your data a good cleaning before trying to use it. Otherwise, you may end up with information that isn’t helpful at all.

Price of Bad Data vs Rise of Good Data

Price of Bad Data vs Rise of Good Data

by | | dataZen

The Price of Bad Data

If the “Customer” data had old or incorrect address, you’d be sending goods ordered to wrong address leading to a dissatisfied Customer, additional shipment charges and administrative/logistic efforts. If “Customer” Master had duplicates, transactions with the Customer would be spread across those multiple duplicate Customer Master records. The whole picture about the Customer (all the transactions) cannot be viewed, as queries would bring only those transactions that happen to be tied to the Master Customer Record. Read loss of cross selling and up selling opportunities. As a Customer Support person, you cannot find the order the Customer is talking about over the phone.

If there were duplicate Item/Material records in the master table, inventory on one of the duplicates would be low, triggering an automatic replenishment, while there was enough stock on hand under a different master record. If Purchasing department ordered on one of the duplicates and Manufacturing department is searching another duplicate’s bin in the warehouse, the situation can lead to productivity loss and lot of shouting over the phone. The purpose of an ERP system can be broken by bad data.

All above confusions can arise in a single ERP system. But generally, organizations have multiple Enterprise Applications in use, with some processes in place to maintain sync of data across the systems. The confusions can grow multifold in this scenario.

The Rise of Good Data

Processes, Data and People run your business. To have good processes, you have a set of Computer Applications to run. You hired the best employees to run your business. Coming to Data, you need to make sure that it is of the highest quality and readily available to all data consumers.

Facilitation of efficient Master data governance with ChainSys

You need to control, monitor and facilitate data creation (Master Data Governance). This will lead to accurate master and transactional data. You should also maintain the quality of data throughout its life on an ongoing basis (Data Quality Management). Quality data is maintained in Operational Systems and as well Data Lakes/Warehouses. The former is called Operational MDM and the later is called Analytical MDM. ChainSys dataZen™ is the right toolset to perform many of the above activities. Unlike the MDM systems and Data Hubs provided by major ERP vendors, dataZen™ is not tied to any one ERP system and is very agile in terms of easily configuring the tool to add meaningful and necessary DQM functions, cross checks on short notice. All systems over time accumulate bad data, which needs periodic cleanup. dataZen™ facilitates pulling a batch of data at a time, subjecting it to established quality checks, getting correction inputs/okays from the right stakeholders and pushing it back into the system. dataZen™ makes MDM fun and easy to do.

Download detailed Smart data features of ChainSys Master data governance rules

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