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The Evolution of Digital Transformation: Tracing Its Historical Journey | Techeela

Explore the captivating history of digital transformation, from its inception to present-day innovations. Uncover how technology has revolutionized industries at Techeela.

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Mastering Data Management: Key Elements of a Modern MDM Platform

Modern data strategies must include master data management (MDM), which supports organizations in preserving data completeness, correctness, and consistency.

Multiple apps and systems throughout an organization can access and exchange master data from a centralized repository provided by an MDM platform. The essential components of a modern MDM platform are as follows:

Data Management

In order to guarantee data consistency, correctness, and compliance, effective data governance is essential. A contemporary MDM platform should have data governance features that let businesses design data policies, establish data quality standards, and keep track of data consumption.

Integration of Data

An MDM platform should include integration features that let businesses combine data from diverse sources, including legacy systems, cloud apps, and third-party data suppliers. ETL, EAI, and ESB are just a few data integration methods a contemporary MDM platform should enable.

Data Reliable

A contemporary MDM platform should provide data quality features that let businesses profile, clean up, and enhance their data. Tools for data quality can find and fix problems in data, standardize data formats, and eliminate duplication.

Master Data Centre

An MDM platform’s central store for master data is known as a master data hub. Organizations can access and exchange accurate and consistent data across the organization because it offers a single source of truth for master data.

Data Privacy and Security

Strong security and privacy controls on an MDM platform are necessary to safeguard sensitive data from unauthorized access and guarantee compliance with data privacy laws. Data encryption, audit trails, and role-based access controls should all be features of a contemporary MDM platform.

Readiness for Clouds

A contemporary MDM platform should be cloud-ready and handle public, private, and hybrid cloud deployment options. MDM deployments benefit from the scalability, flexibility, and affordability of cloud deployment.

Conclusion

In conclusion, a modern MDM platform should support cloud computing and contain features like data governance, integration, quality, a master data hub, and data security and privacy. By using a contemporary MDM platform, businesses may increase their business agility and decision-making skills while maintaining data accuracy, consistency, and completeness. Source: https://medium.com/@digipyadav/mastering-data-management-key-elements-of-a-modern-mdm-platform-f37d049987b8

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Exploring the Benefits of IBM Watson Analytics: Turning Raw Data into Actionable Insights

IBM Watson Analytics is a cutting-edge technology for data analysis and visualization that enables companies to transform unstructured data into insights that can be put to use. The tool’s purpose is to assist firms in making wise decisions and enhancing overall performance. We shall talk about the advantages of IBM Watson Analytics in this article.

1. Simple to use

The simplicity of usage of IBM Watson Analytics is one of its main advantages. The tool’s user-friendliness and intuitiveness make it possible for non-technical individuals to deal with data.

Users may swiftly import data from a variety of sources, including spreadsheets and databases, thanks to the user-friendly and intuitive interface. Additionally, the tool comes with a variety of pre-made dashboards and templates, making it simple to get started and visualize data.

2. Powerful Analytics Abilities

IBM Watson Analytics is an effective tool for data analysis that may assist companies in finding patterns and insights in their data. The programme has a variety of analytics features, such as natural language processing, data visualisation, and predictive modelling. With the help of these tools, businesses may find patterns and trends in their data and base choices on those insights.

3. Comprehensive Data Visualization

A variety of data visualisation tools are provided by IBM Watson Analytics, making it simple to produce eye-catching data visualisations. Users can select from a variety of chart kinds and designs and alter their visualisations to suit their own requirements. The programme also has sophisticated mapping features that let users view data spatially.

Conclusion

In conclusion, IBM Watson Analytics is an effective and user-friendly solution for data analysis that may assist companies in transforming raw data into useful insights. The product is perfect for businesses of all sizes looking to enhance their data analysis and decision-making processes because of its extensive analytical capabilities, user-friendly interface, and collaboration features.

Source: https://medium.com/@digipyadav/exploring-the-benefits-of-ibm-watson-analytics-turning-raw-data-into-actionable-insights-6aa761b006e1?postPublishedType=repub

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Data Modernization and AI in Banking: Revolutionizing the Industry

Data modernization & AI have recently revolutionized the banking sector, allowing banks to work more effectively, and deliver superior customer experiences which help in making more informed decisions. There are some positive impacts of data modernization on the banking industry.

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Importance of AI Fraud Detection in Banking

Regulatory requirements compliance

Several regulatory requirements, including the know-your-customer (KYC) and anti-money laundering (AML) laws, must be complied with by banks. By examining client information and transaction patterns to find potential hazards and suspicious behavior, AI-based fraud detection in banking systems can assist banks in adhering to these requirements. Maintaining customer confidence and preventing exorbitant fines depend on compliance with regulatory regulations.

Reduced False Positive Rates

When a valid transaction is misclassified as fraudulent, this is known as a false positive. Customers may become angry as a result of these false alarms, and banks may incur higher operating expenses. By continuously learning and adjusting to new patterns and anomalies, AI systems can assist in lowering the number of false positives. As a result, the system’s accuracy is increased and the frequency of false alerts is decreased.

Regulatory requirements compliance

Several regulatory requirements, including the know-your-customer (KYC) and anti-money laundering (AML) laws, must be complied with by banks. By examining client information and transaction patterns to find potential hazards and suspicious behavior, AI-based fraud detection can assist banks in adhering to these requirements. Maintaining customer confidence and preventing exorbitant fines depend on compliance with regulatory regulations.

Reduced False Positive Rates

When a valid transaction is misclassified as fraudulent, this is known as a false positive. Customers may become angry as a result of these false alarms, and banks may incur higher operating expenses. By continuously learning and adjusting to new patterns and anomalies, AI systems can assist in lowering the number of false positives. As a result, the system’s accuracy is increased and the frequency of false alerts is decreased.

For the banking sector to avoid financial losses, safeguard consumer data, adhere to legal requirements, and minimize false positives, AI-based fraud detection is crucial. Banks may improve customer trust and avoid expensive penalties by investing in AI-based fraud detection systems that can efficiently identify and prevent fraudulent actions.

Conclusion

For the banking sector to avoid financial losses, safeguard consumer data, adhere to legal requirements, and minimize false positives, AI-based fraud detection is crucial. Banks may improve customer trust and avoid expensive penalties by investing in AI-based fraud detection systems that can efficiently identify and prevent fraudulent actions.

Source:https://medium.com/@digipyadav/importance-of-ai-fraud-detection-in-banking-44001ac388c6

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Importance of AI Fraud Detection in Banking

Regulatory requirements compliance

Several regulatory requirements, including the know-your-customer (KYC) and anti-money laundering (AML) laws, must be complied with by banks. By examining client information and transaction patterns to find potential hazards and suspicious behavior, AI-based fraud detection in banking systems can assist banks in adhering to these requirements. Maintaining customer confidence and preventing exorbitant fines depend on compliance with regulatory regulations.

Reduced False Positive Rates

When a valid transaction is misclassified as fraudulent, this is known as a false positive. Customers may become angry as a result of these false alarms, and banks may incur higher operating expenses. By continuously learning and adjusting to new patterns and anomalies, AI systems can assist in lowering the number of false positives. As a result, the system’s accuracy is increased and the frequency of false alerts is decreased.

Regulatory requirements compliance

Several regulatory requirements, including the know-your-customer (KYC) and anti-money laundering (AML) laws, must be complied with by banks. By examining client information and transaction patterns to find potential hazards and suspicious behavior, AI-based fraud detection can assist banks in adhering to these requirements. Maintaining customer confidence and preventing exorbitant fines depend on compliance with regulatory regulations.

Reduced False Positive Rates

When a valid transaction is misclassified as fraudulent, this is known as a false positive. Customers may become angry as a result of these false alarms, and banks may incur higher operating expenses. By continuously learning and adjusting to new patterns and anomalies, AI systems can assist in lowering the number of false positives. As a result, the system’s accuracy is increased and the frequency of false alerts is decreased.

For the banking sector to avoid financial losses, safeguard consumer data, adhere to legal requirements, and minimize false positives, AI-based fraud detection is crucial. Banks may improve customer trust and avoid expensive penalties by investing in AI-based fraud detection systems that can efficiently identify and prevent fraudulent actions.

Conclusion

For the banking sector to avoid financial losses, safeguard consumer data, adhere to legal requirements, and minimize false positives, AI-based fraud detection is crucial. Banks may improve customer trust and avoid expensive penalties by investing in AI-based fraud detection systems that can efficiently identify and prevent fraudulent actions.

Source: https://medium.com/@digipyadav/importance-of-ai-fraud-detection-in-banking-44001ac388c6

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Data Modernization Initiatives in Banking Takes on New Urgency

Benefits of Data Modernization in Banking

Banking legacy system data modernization initiatives can have a number of advantages, such as:

1. Efficiency gains: Legacy systems are frequently out-of-date and inefficient, which can result in lengthy processing times and higher expenses. Modernizing these systems can help banks operate more efficiently and spend less money.

2. Improved customer experience: By adding new features and services as well as faster and more accurate information, updating outdated systems can give customers a better overall experience.

3. Increased adaptability: Because legacy systems can be challenging to update or modify, banks may find it challenging to respond to changes in the market or the regulatory landscape. By updating these systems, banks may find it simpler to react rapidly to changes and new difficulties.

4. Enhanced data security: Due to outmoded security measures, legacy systems may be more susceptible to cyberattacks and data breaches. Banks can increase their data security and threat protection by modernizing these systems.

Source:https://medium.com/@digipyadav/data-modernization-initiate-in-banking-takes-on-new-urgency-ab7e94abf490

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Data Engineering Beginner’s Guide

Here is a starting point for the complicated and ever-evolving discipline of data engineering:

Know the fundamentals of data engineering: Designing and building data pipelines to gather, process, and store huge amounts of data is data engineering. Order to assist data analysis and business intelligence also entails the creation of data models and the use of database technology.

Learn programming languages and tools: Python, SQL, and Java are just a few of the computer languages that are needed for data engineering. It’s also crucial to be familiar with database technologies like SQL Server, MySQL, and MongoDB. Data engineers employ a number of tools, including Apache Kafka, Apache Spark, and Apache Airflow, to create data pipelines.

Study big data technologies: With the amount of data increasing, it’s critical to be knowledgeable about big data technologies like Hadoop, Spark, and NoSQL databases. Data engineers can efficiently handle massive amounts of data thanks to these technologies.

Knowing data governance is important since it entails controlling the security, usability, availability, and accuracy of the data utilized by an organization. To make sure that the data pipeline they create conforms with laws and corporate standards, data engineers should be familiar with data governance policies and procedures.

Develop soft skills: Data engineers must be able to speak clearly with project supervisors, business analysts, and data scientists, among other stakeholders. You’ll excel in this profession if you acquire soft skills like communication, teamwork, and problem-solving.

Keep learning: Data engineering is a discipline that is always changing. Attending conferences, webinars, and training sessions will help you stay current on the newest trends and technologies.

Conclusion

To sum up, data engineering is a challenging field that demands both technical and soft abilities. You may succeed as a data scientist by learning the basic principles of data engineering, picking up languages such as Python and tools, mastering data modeling techniques, picking up on big data technologies, mastering data governance, and honing soft skills.

Source: https://medium.com/@digipyadav/data-engineering-beginners-guide-b7330c56145f

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The Future of Digital Marketing (Updated Guide) 

With the emergence of a digital era, the marketing landscape has grown to become versatile and immersive. It’s an ecosystem under constant change, making it imperative to keep on top of trends. Importantly, it allows you to be of benefit to your brand, and also – to a large degree – the clients and businesses you’re involved with. 

As we recover from the pandemic with hopes of finding a better year in 2021, we notice the importance weighed into user or unified customer experience, facets that focus on micro-moments, highly targeted advertising, and functionality. But that’s not all; in most cases, these innovations run through a constant process of refinement – AI-driven, mostly. 

But given all the advancements, where exactly does the future of digital marketing in future stand with next-generation technologies or is digit? What combines them, or better yet, what are the factors we ought to keep an eye on moving further into 2021 and beyond? Let’s take a look at all these and what’s new in digital marketing. 

Top 5 Features that Define the Future of Digital Marketing 

1. Artificial Intelligence 

Even within the siloed context of digital marketing, the field of artificial intelligence is rather broad. In the marketing context, AI usually fits into the meta-analysis of broad-spectrum data sets and using said data sets to make business decisions. Despite the technology still being in its infancy, we live in a world with examples stemming from our day-to-days. 

For example, Netflix and Amazon have built-in AI features that help with transactions and recommendations. The future of AI in digital marketing has endless possibilities, with face and voice recognition, digital assistants, content creation, chatbots, and targeted marketing strategies and marketing agencies. It is expected to become the norm with respect to marketing strategies due to its spectacularly accurate ability to analyze consumer behavior, which in turn feeds into something more personalized and interactive. 

2. AI-Powered Digital Assistants 

Think Google Assistant or Alexa for starters. AI-powered digital assistants are designed to stay connected to people and assist with functions in their day-to-days. The market on these personal assistants is predicted to reach roughly 1.6 billion users by 2020. In fact, devices made by different companies are even able to connect with each other for information; they are, in a way, collaborating. 

On the other hand, users will be given the opportunity to watch AI evolve on a business and personal level. AI-based technologies are pacing to improve at a rapid pace, including voice recognition and other personalized services – based on the data analysis of consumer behavior. 

3. A Shifting Social Media 

It is more about how we are beginning to use social media as a platform, as a variation to its original purpose. What once started as a platform for peer-to-peer interactions has now evolved into a place of entertainment, with users watching more videos or digital media than specifically using them for social purposes. Additionally, users are now beginning to increasingly demand a more user-focused and less ad-focused means of interacting with peers or being entertained. 

This urges marketers to keep an eye on how social media platforms choose to incorporate new and explicit advertising strategies, in addition to understanding smart and implicit methodologies to collecting customer information. 

4. OTT 

From the silver screens to the smallest of screens, watching movies have undergone a significant evolution. Owing to the Covid-19 pandemic that swept across the world and made it immobile for nearly a year, OTT has become a part of most households. With Netflix, Apple TV and Amazon prime ruling the world, there is a gamut of international to national and regional options to choose from, depending on the consumer’s budget. 

The platforms have also given rise to a plethora of content and talent pool who earlier had limited scope. Marketers have already begun their journey in this domain, with targeted advertisements for their consumers. The future scope of digital marketing in OTT is ample, and it will be worth the wait to see the growth of this platform! 

5. Augmented Reality 

Remember the craze around Pokemon Go and Google AR animals not so long back? The future of online marketing looks bright in augmented reality. A unique experience is created when artificial elements extracted from imagination and the real world are juxtaposed. 

In recent times, it has become one of the most exciting technologies in which marketers love engaging their consumers. It has brought about a shift in the way marketers predicted consumer behavior. From games, to healthcare, real estate, and more, augmented reality apps soon will broaden the scope of digital marketing in the future. 

Conclusion: 

To sum up, with the growing numbers of smartphones and digital footprint, the future of digital marketing looks very radiant. Marketers are becoming more agile and making decisions faster driven by data. 

SOURCE: https://www.reddit.com/user/diehardtechlover/comments/12lsex7/the_future_of_digital_marketing_updated_guide/

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Customer Experience Management: What It Is and Why Does it Matter?

What are the metrics for measuring an organization’s success? Customer experience management, i.e., how the business handles its interaction with customers to build a better experience for them. 

Based on an analysis carried out by Brain & Company, there was an upsurge of 4%-8% in revenue for companies with superior customer experience management. 

To put it simply,

Companies that believe in the importance of customer experience management and adopt strategies to improve it have achieved higher customer satisfaction, reduced customer abandonment rates, and increased revenue. 

This is just one reason why creating a great customer experience is key to the success of your business and why you should prioritize it.  

Here in this blog, we’ll walk you through customer experience management, why it is essential, how to measure customer experience, and challenges, and how you can create a good customer experience.  

So, let’s get started. 

What is Master Data Management?

Customer Experience is often directed to CXMṣ or CEM.  

It refers to your customer’s interactions with your business throughout the customer experience journey, beginning with their first contact and continuing until they become happy, loyal customers. 

Creating an exceptional customer experience is a two-step process that involves two primary touch points: people and products.

In a nutshell, CEM is a way of understanding the needs of your ideal customers, communicating with them, serving them, and making sure they are satisfied throughout the entire purchasing process. Customer experiences are the sum of their interactions with a brand or company throughout a relationship. 

Importance of Customer Experience Management

There is no doubt that customer experience management is one of the most critical factors for the success of a business. 

Providing an excellent customer experience is not just about putting on a good show and getting good press. By making technology more human and incorporating your customers’ experiences, you can create a win-win situation that benefits you and your customers. 

As the global marketplace becomes more competitive and hyperconnected, customer experience becomes more crucial. In addition to generating leads and converting them into customers, businesses have the opportunity to develop rich, personalized experiences and build long-term relationships with their customers. 

An organization that adopts a good customer experience business model can reap many benefits. As an example, we will discuss some of the benefits of customer management experience are below: 

A Higher Level of Customer Satisfaction 

When your interactions with customers are better tailored, you’ll experience fewer gaps in the customer experience that leave you open to criticism.  

By defining the customer experience based on effort, emotion, and intent, you will be in a position to provide a product or service that is truly exceptional. You will achieve higher levels of customer satisfaction if you tailor your customer interaction to the individual.   

Customers Can be Better Known by Businesses 

Understanding and knowing the customer’s needs is the cornerstone of every successful business, whether it sells directly to consumers or indirectly. The better you understand your customer’s journey, the better you can design a path that will lead to success.  

The Opportunity to Generate More Revenue 

As we have already mentioned, if you give your customers the kind of service they deserve and are satisfied, they are more likely to return. According to multiple studies, loyal customers are more likely to increase revenue over time by 300 percent compared to non-loyal customers. 

Furthermore, loyal customers are essential in spreading the word about your brand throughout the community and bringing on new customers through referrals. Your organization’s revenue increases as a result of all of these factors. 

An Excellent Customer Experience Results in an Engaged Workforce 

It might surprise you that customer experience management has a positive impact, but it’s true. It is believed by several studies that a great customer experience will result in 1.5 times more engaged employees, as well as higher productivity. 

The workforce’s productivity is one of an organization’s most important assets. 

Reduce Churn Rates 

An organization’s churn rate is generally the number of customers who discontinue doing business with the brand or company in the short or long term.  

Consequently, reducing your churn rate means that you will lose a smaller number of customers and be able to keep more of your existing clients on board. 

Improves the Customer’s Loyalty and Advocacy for Your Business 

Your chances of repeat business will increase if you can get your customers’ loyalty. By putting your brand in front of the right people, you can enhance its visibility, build strong brand awareness, and increase sales. 

Measuring Customer Experience: How to Do It?

Getting a competitive edge requires understanding customer experience throughout the customer journey, analyzing the results, and improving customer service based on the insight.  

Here we have shared the different metrics to measure customer success.  

Let us begin. 

An Assessment of the Overall Customer Journey 

An excellent place to begin within the measurement process is by assessing the overall customer journey.  

When measuring the customer journey, two metrics can be utilized: the Net Promoter Score (NPS) and the Customer Effect Score (CES). 

We’ll introduce you to these two metrics below: 

Net Promoter Score (NPS) 

A meaningful way to measure a company’s overall experience is to calculate its Net Promoter Score or NPS. 

An NPS score measures how likely a customer is to recommend a brand to acquaintances and family members. 

Simply put,  

NPS is the way to determine the loyalty and advocacy of customers. 

In addition to considering products, prices, onboarding, marketing, and touchpoints, NPS illustrates your overall customer experience. 

Customer Effort Score (CES) 

As the name suggests, the Customer Effort Score (CES) measures how much effort customers need to put forth to achieve their goals when using a product or service. A number of activities are involved in this process, including purchasing products, answering questions, fixing issues, or returning goods. 

Whenever you want to determine the Customer Effort Score, you will need to launch a survey that gives the respondents a choice of either agreeing or disagreeing with the statement suggested by the company.  

2. Customer Churn Rate 

A churn rate can be defined as the percentage of your customers who leave your business over time or are no longer interested in the products or services you offer. 

When you experience a high churn rate, you are losing most of your customers, making it harder to grow your business further.

3. Customer Retention Rate 

In contrast to the churn rate, the retention rate measures how many customers stay loyal to your business over time and continue paying for products or services. 

Make sure you keep an eye on the customer retention rate regularly so that you can determine if the retention rate is on the rise or the decline. If the retention rate declines, take prompt action to avoid losing the business. 

4. Measure the Number of Customer Support Tickets Received and Resolved 

There are many ways to measure customer satisfaction, but one of the most direct ways is by counting the number of support tickets received. 

For instance, if you receive more tickets than usual, you must create an effective customer experience management strategy. In the case of recurring hiccups across tickets, investigate possible causes for them and how you can fix them. This will allow you to decrease the number of tickets your customer service representatives receive while maintaining a positive customer experience.  

5. Referral Rate of Customers to Other Customers 

A Net Promoter Score (NPS) represents the percentage of customers willing to recommend your product or service to their friends and family members. The referral rate, on the other hand, indicates how many customers are recommending your business to their friends and family.  

Customer referrals can be seen as proof that you have a quality product worth investing in, so it is also worth recommending to friends and colleagues. To increase your referral rate, you must first ensure that your customers have a positive experience during their time with your company. 

6. Average Resolution Time (ART) 

Creating a positive customer experience is one of the most critical business goals that can only be achieved by establishing an effective support system that stands side by side with your customers at every step. 

But how will you gauge the efficiency of your customer support team?  

This is when Average Resolution Time (ART) plays an important role.  

The ART represents your customer service team’s average time-solving customer problems. Support queries take varying amounts of time to resolve; some might take more time while others take less. 

Don’t Let Your Customer Experience Metrics Go to Waste

Measuring customer experience is essential to ensure your business grows steadily by making the necessary improvements. However, you will not be able to do so without a compelling customer experience management strategy. 

These metrics will allow you to discover a variety of information about your customers and your products, such as how seamless your product is, how easy it is to use, and many more. Besides that, they will also be able to identify valuable insights that they can use to improve the quality or performance of their products and services in the future. 

These advantages can benefit a business in many ways, including lowering churn rates, increasing customer retention rates, etc. 

Using the Average Resolution Time (ART), companies can also identify their most effective teams and where improvements could be made. It would be equally possible to measure the same for your product and service. 

Your business can benefit greatly from knowing how your customers use your product. The more you know about them, the more beneficial changes you can make, and the more delightful your customers’ experiences will be.  

Shortly, these metrics will provide leadership teams with the ability to gain complete visibility into critical areas of customer experience management that positively or negatively affect your organization’s success. 

If you have trouble keeping track of these metrics, you can rely on customer experience management software. It is an excellent way to monitor and analyze the experience that customers have with your business. This software can also provide you with necessary improvements that can be made to enhance the customer experience and business model. 

Source: https://www.reddit.com/user/diehardtechlover/comments/12jfphx/customer_experience_management_what_it_is_and_why/?utm_source=share&utm_medium=web2x&context=3

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Data Strategy Components, Strategy & Benefits

Components of Data Strategy: Data Strategy provides a custom-built solution for every business. Some basic types of data strategies are Federal and Enterprise data strategies, which just denote the usage purpose of that strategy.

The basic need of data strategy is

Increase in Data Volume

Data Quality

Data Security and Governance

Collaborative Efficiency

Source: https://www.reddit.com/user/diehardtechlover/comments/12ibxqe/data_strategy_components_strategy_benefits/

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A Data Engineering Beginner’s Guide for Roles & Responsibilities 

Data engineering helps enterprises to enhance their customer-related services and improve their business processes. Read this data engineering guide about data engineering roles, responsibilities, challenges and scope of data engineering in future. 

Source: https://www.reddit.com/user/diehardtechlover/comments/12dgnie/a_data_engineering_beginners_guide_for_roles/ 

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Importance of Data Curation in Data Warehouse

Data curation involves creating valuable data for users engaged in discovery and data analysis. It includes gathering, maintaining, and managing data in databases or data warehouses to make it useful.

Data curation characteristics include identifying signals, robust data management throughout the data cycle, and supporting data governance.

Source: https://www.reddit.com/user/diehardtechlover/comments/12cdmhw/what_is_data_curation_and_its_benefits_for/

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A comparison between different BI analytics tools - IBM Cognos, Power Bi & Tableau

In business, data and trends work sideways. We often rely on past data to forecast future trends for our business. There are 3 famous BI analytics tools - IBM Cognos, Power Bi & Tableau which are used by different businesses.

Visit: https://techeela.com/bi-reporting-tool/ to know more about it's comparison in detail.

Source: https://www.reddit.com/user/diehardtechlover/comments/12adb7e/a_comparison_between_different_bi_analytics_tools/

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What is Data warehouse? Types & Benefits

Data Modernization

Get to know about about types of data warehouse and which is best suited for your organization. It is a key factor in achieving your goals and objectives as an organization.