Weekly questions to consider when creating your posts. These questions are a jumping off point to asking your own questions, pose new ideas, and provide explanations and examples backed by careful analysis. Apply class concepts, terms, and theories too. Refer to Assignment 12 for additional details.
- What are descriptive and predictive analytics?
- What separates data from big data?
- Why do companies use big data?
- What is business intelligence, and how does it help companies?
- What are the differences between OLTP vs. OLAP, and what are some examples of each?
- What are the types of data?
- What are the sources of data?
- What is supply chain management and how does it affect businesses?
- Why are supply chains fragile?
- What is RFID, and how does it help supply chain management?
Lancelot Nyandoro says
What is RFID, and how does it help supply chain management?
It is Radio-frequency identification, it identifies are within the system and could track for example staff tags in hospitals and and the GPS in your car
Marie-Christine Martin says
Example
Darren Nolan says
Post
Descriptive analysis is more analysis with words rather than numbers. It’s taking data and interpreting it and telling you what it is and means in words. When you can do that to data you will do your job very well because once you understand what you are doing then you will never get anything wrong. While predictive analysis is taking numbers and yes doing the same with descriptive to a degree but also using the data to see what will happen in the future. Also seeing what will happen and using that to make adjustments that will benefit your company. Like if you see notice that at then time off the year your product has a less of demand as the rest of the year then you will know to make less of your product so your not wasting money on supply.
Darren Nolan says
Very straight to the point maybe an example would help at least me understand more what you are saying.
Lancelot Nyandoro says
What is business intelligence, and how does it help companies?
It is the proper collection of data.
It helps them make better decisions when it comes to forecasting sales, purchasing and marketing waves
Hadeer Saad says
Hello Lancelot,
Intelligence data is fundamental, especially if you are running a big company. Big companies struggle with making significant decisions, so intelligence data comes in handy for them.
Mairaliz Negron says
Hi Lancelot,
Such a simple yet good informative definition of what Business Intelligence is. I would say it is definitely a powerful and useful tool to help continue or improve success within a company or business. I personally think that this tool has been a game changer in the business world.
Colin Johnson says
Descriptive and predictive analytics are two fundamental branches of data analysis that empower organizations to derive meaningful insights from their data.
Descriptive analytics focuses on summarizing historical data to provide a clear understanding of what has happened in the past. It involves the examination of patterns, trends, and key performance indicators to gain insights into historical performance. This form of analysis is crucial for businesses to comprehend their current situation and make informed decisions based on past occurrences.
On the other hand, predictive analytics involves using statistical algorithms and machine learning techniques to forecast future outcomes. By analyzing historical data, predictive analytics identifies patterns and trends that can be extrapolated to predict future events. This forward-looking approach enables businesses to anticipate trends, make proactive decisions, and optimize strategies for better outcomes.
In essence, while descriptive analytics explains what happened, predictive analytics goes a step further by providing insights into what is likely to happen, empowering organizations to make informed decisions and stay ahead in a dynamic environment.
Corey Reagan says
Colin,
That was a well written post and had great detail on the subject. I love when I can learn something new by reading some of these posts, and I did from yours. Great post!
Georgios Zisis says
Hi Colin,
You did a great job of explaining what descriptive and predictive analytics are and how they work together! These analytics together also help companies enhance their efficiency, plan strategically, and ultimately continue to improve.
Corey Reagan says
What is RFID, and how does it help supply chain management?
RFID, which stands for Radio Frequency Identification, is a technology used for the identification and tracking of objects using radio waves. It is a wireless communication technology that allows data to be transmitted and received between a tag, also known as an RFID tag, and a reader. It has revolutionized supply chain management by providing real-time observation and accurate inventory tracking. This technology enables businesses to streamline operations, optimize inventory levels, prevent stockouts, and enhance customer satisfaction. By facilitating seamless communication between suppliers, manufacturers, distributors, and retailers, Its ability to read multiple tags simultaneously, track individual items in real-time, store and transmit a large amount of data, withstand harsh environmental conditions, and promote automation makes it indispensable.
Regan DeShazo says
Overall, RFID contributes to supply chain optimization by providing real- time data, minimizing manual intervention, and improving the overall efficiency and reliability of logistic an inventory processes.
Madison Masino says
I thought RFID was very interesting as we witness it everyday when shopping. It’s used in many commercial and and industrial applications. I also read how there can be RFID theft but more-so in Europe as they have rfid credit cards.
Dana Persaud says
Great point! Many people prefer to have RFID proof passport holders and wallets for storing credit cards when traveling. With a new rise in technology there are always unexpected improvements that need to be made,
Zarmina Khan says
Hi Corey, I was confused about RFID and how it aids the supply chain management aspect of things, but reading your analysis of it really helped. Illustrating how businesses streamline operations, optimizes inventory levels, and prevent stockout’s is definitely a useful tool whether or not you are in the supply chain management field, but could relate directly to owning a business or being someone who might want to.
Lancelot Nyandoro says
Yes, Corey! We use and sell RFID at my job. in use, it tells us where something is such as stock/inventory, and for the companies we sell it to, which is hospitals, they use it to locate things like defibrillators which has helped and saved many lives
Regan DeShazo says
What separates data from big data?
The key distinction between data and big data lies in the volume, velocity, variety, and complexity of information. While traditional data refers to structured and manageable datasets that can be easily processed by conventional databases, big data represents vast and diverse sets of information that exceed the capabilities of traditional data processing methods. Big data encompasses massive volumes of data generated at high velocities from various sources, including social media, sensors, and transaction records. Additionally, big data is characterized by its variety, comprising structured, semi-structured, and unstructured data types. The complexity of big data arises from the need to analyze and extract meaningful insights from diverse data formats and sources. The advent of big data technologies, such as distributed computing frameworks and advanced analytics tools, enables organizations to harness the potential of these large datasets for strategic decision-making, predictive analysis, and uncovering patterns that might be otherwise difficult to discern in traditional data processing environments.
Colin Johnson says
Your blog post brilliantly outlines the distinctions between traditional data and big data. The key differentiators – volume, velocity, variety, and complexity are explained very well. Your post also emphasizes the role of technological advancements, like distributed computing, in harnessing the power of big data for strategic decision-making. This was a clear and insightful perspective on the evolving landscape of data processing.
Zarmina Khan says
Hi Regan, understanding how big data differs from data flew over my head, not gonna lie, but the way you described it here is alot more concise and helped me in understanding it more than I did before. The complexity of big data and the need to analyze and extract meaningful insights from diverse data formats, definitely aid one another more than apart.
Hadeer Saad says
Hey Regan,
Great work! It’s essential to understand the differences between traditional data and big data. Your post helped me understand it better!
Madison Masino says
Supply chain management is the process itself of the flow of goods and services. When asked how does it affect business, I would say that business revolves around the supply chain. If you are a business with product that needs to be distributed and sold, than you depend on the supply chain to get your products where they need to be. Personally, I think the supply chain is one of the most important aspects of the business world. I think it relates to our class specifically because those who work within direct relation to the supply chain, they must do inventory and such which that data can be kept on a website, even on excel.
Leanne Sheely says
I agree with you that supply chain is definitely one of the most important aspects. I know especially during covid we all saw that. Crazy how stores really ran out of toilet paper and that become a supply chain issue.
Ajibola Sode says
Hey Madison,
You are absolutely right in placing emphasis on the pivotal role of supply chain management (SCM) in the business ecosystem. SCM has a significant impact on almost every aspect of a business, ranging from procurement to product delivery. Its efficiency has a direct impact on the bottom line of a business. SCM is critical to businesses in several ways, and it is closely related to the broader context of operations, such as data management and technological integration.
Zarmina Khan says
What are descriptive and predictive analytics
Descriptive analyics and predictive analytics are two types of data analysis that serve different purposes in gaining insights from data. Descriptive analytics’s purpose is concerned with summarizing and describing historical data to provide a clear picture of what has happened prior. Understanding patterns and trends is very important. It’s method consists of different statistical and visual techniques. Generating reports on past sales performance, website traffic patterns, and customer feedback are all prime examples. Predictive analytics on the other hands purpose is to look forward and forecast future trends, behaviors and outcomes based on historical data and statistical algorithms. It’s method would be machine learning, statistical modeling, and data mining techniques. Some examples would include future sales, inventory needs, determining maintenance schedules.
Danylo Pidkova says
Hi Zarmina,
Great examples! I think that descriptive analytics is about the the past. It helps make reports on past sales or website traffic. Predictive analytics, on the other hand, looks to the future. It forecasts trends using historical data and methods like machine learning.
Leanne Sheely says
What is business intelligence, and how does it help companies?
Business intelligence is kind of like AI but for primarily business information. It is a technology that helps analyze the business information to help you make a business decision. BI won’t tell you what decision to make or what the outcome will look like if you make that decision. It helps you to understand the information it’s giving you so that you are able to make a more educated decision.
This helps companies by helping their employees understand data that they are seeing better. BI is something so simple as a report or a visualization of something. You probably have seen more BI related items then you thought. Some of business intelligence’s top tools are Domo, Dundas BI, Microsoft Power BI, MicroStrategy, Oracle Analytics Cloud, Qlik, SAS, Sisense, Tableau, and Tibco. Hopefully that can help ring a bell for you if not now you know some BI tools to use!
Juan Delgado says
Hi Leanne,
Nice response! I enjoyed this response because you used examples with your discussion board. Most of the time I don’t understand the concepts until I see examples, so that helped me. Also, your going into detail about business intelligence helped.
Mairaliz Negron says
Hi Leanne,
I also chose this question. I found your response to be a great analysis and breakdown of what Business Intelligence is. Also, great emphasis on explaining that Business Intelligence itself won’t tell you what it is that you have to do or what decision to make, this strategy is all about analyzing the information that is provided to you yourself to be able to make a better informed decision
Ajibola Sode says
Why do companies use big data?
Big data is used by companies to improve decision-making, gain customer insights, enhance operational efficiency, create a competitive advantage, manage risks, drive innovation, perform financial analysis, optimize supply chain management, monitor health and safety, and respond in real-time. By analyzing large volumes of data, companies can gain insights that lead to sustainable growth.
Elena Grigoryan says
Big data is a great tool for many businesses. It allows to gain many useful insights about business clients, existing or potential.
Ajibola Sode says
Moreover, big data enhances the monitoring of health and safety, allowing businesses to predict potential hazards and bolster workplace safety measures.
Furthermore, one of the standout advantages of big data is its capacity for real-time responsiveness. In the dynamic environment of today’s market, the capability to swiftly adjust to shifts in market dynamics, customer preferences, and external challenges is crucial for a company’s success. Big data equips businesses with the agility and responsiveness necessary to stay competitive, ensuring they can not only reach but also maintain long-term growth.
Danylo Pidkova says
Why are supply chains fragile?
Supply chains can be fragile due to several interconnected factors, making them vulnerable to disruptions and challenges. Some key reasons include:
Globalization: Many supply chains are extended across the globe to take advantage of cost efficiencies. However, this also means they are exposed to risks such as geopolitical tensions, trade disputes, and natural disasters in different regions.
Complexity: Modern supply chains often involve numerous interconnected suppliers, manufacturers, distributors, and retailers. The complexity of these networks can make it difficult to identify and mitigate potential risks effectively.
Single Sourcing: Depending on a single supplier for critical components or materials can lead to vulnerabilities. If that supplier faces disruptions, the entire supply chain may be affected.
Dependency on Technology: While technology enhances efficiency, it also introduces risks. Cybersecurity threats, software glitches, or system failures can disrupt operations and impact the entire supply chain.
Pandemics and Health Crises: Events like the COVID-19 pandemic highlighted the vulnerability of global supply chains to health-related disruptions. Such events can lead to factory closures, transportation restrictions, and workforce shortages.
To address these challenges, businesses are increasingly focused on building more resilient and flexible supply chains by diversifying sourcing, investing in technology, enhancing visibility, and adopting risk mitigation strategies.
Juan Delgado says
Hi Danylo,
I enjoyed how you explained the concept of why supply chains are fragile. The reason I enjoyed this post was because you explained every single reason that could’ve been to answer the question. This made me understand the concept. I also just liked how this post was set up on how you answered the question, gave all of the reasons, and then concluded. The post flowed very well.
Salvatore Marsico says
Hi Danylo,
I liked reading your post and all of the information provided. I like how you provided how to address the challenges faced with dealing with pandemics and health crises. When COVID happened, it was a big issue but hopefully increased focused on building more resilient and flexible supply chains will solve the issues these challenges provide.
Juan Delgado says
What is RFID, and how does it help supply chain management? RFID is radio frequency identification, which is wireless technology. It enables identification with objects that have special RFID tags. One of the things that RFID helps supply chain management is that it does inventory control and access control. One example of this is with debit and credit cards within the last couple of years. A lot of cards have been having a tap function. Where you can just put your card to the card machine and it just reads that it is your card within a matter of seconds. For supply chain management, it is helpful to not have your card get stolen. Since it would be harder for scammers to steal your card. When we used to insert our cards, someone had put something in the card machine to steal our card’s information. But, with the tap function, it is harder since it is only a tap function that takes only a couple of seconds.
Salvatore Marsico says
Hi Juan,
I enjoyed reading your post about what RFID is and how it helps supply chain management. It is really interesting how RFID does inventory control and access control which is basically like debit and credit cards. The information you provided is very useful and helpful to understand the material.
Hawa Barry says
Hi Juan,
Nice explanation of RFID. It’s definitely becoming more common to see cards with tap, and similar to inserting canceling out swiping a card, the tap function is becoming the default/dominant card method for POS systems to recognize.
Salvatore Marsico says
Descriptive analytics is comprised of two methods known as data aggregation and data mining, but first, descriptive analytics is the analysis of historical data. The two methods are used for uncovering trends and patterns. Descriptive analytics is about studying what has happened in the past, but not making predictions about the future. Descriptive analytics are mostly viewed using visual data representations such as line, bar, and pie charts, which may be a foundation for future analysis. Predictive analytics is sometimes viewed as a more advanced method of data analytics because it uses probabilities to basically predict the future. Predictive analytics uses statistical modeling and machine software to point out the likelihood of future outcomes.
Business Intelligence is composed of sets of strategies and technologies businesses use to analyze business information and to conform it into reachable perceptions that can inform strategic and tactical business decisions. Business Intelligence helps companies by making data-driven business decisions, faster analysis and intuitive dashboards, increased organizational efficiency, improved customer experience, improved employee satisfaction, trusted and governed data, and increased competitive advantage.
Max Smith says
Hi Salvatore,
I thought your description of both descriptive analytics and business intelligence was excellent. In addition, your description of the elements that go into descriptive analytics and business intelligence helped better understand the concepts.
Mahbuba Ahmed says
Hi Salvatore
Your explanation the distinction between descriptive analytics and predictive analytics was great, highlighting their focus on past events and future predictions, respectively. In addition, it explains Business Intelligence, emphasizing its role in making data driven decision, enhancing efficiency, and improving overall business performance.
Ereny Abousaif says
Hi Salvatore,
You did a great job describing both business intelligence and descriptive analytics, in my opinion. Furthermore, your explanation of the components of business intelligence and descriptive analytics made the ideas easier to understand.
Georgios Zisis says
What is supply chain management and how does it affect businesses?
Supply chain management is the flow of goods, services, information and the processes from start to finish. Some of these processes include any sourcing, production, logistics, information systems, or customer service required for the product to make it to the customer. As you can see, there are many steps and processes in the supply chain. Any interruptions during the process can affect a business and this is why supply chains are fragile.
I think this is a perfect example to connect back to ERP and CRM. Enterprise resource planning (ERP) is a software system that helps a company run the entire business. ERP is very important software for companies to make sure the their fragile supply chain is not interrupted. Any issues during the supply chain can create a delay and a loss in profit. Customer relationship management (CRM) is a software that helps an organization create and maintain a strong relationship with current and future customers. The end goal of supply chain is to get a product to the customer. Before a company can think about being profitable, they must have customers. CRM helps retain customers by providing customer information to the marketing and HR teams. With this information, marketing is able to send personalized messages and promotions to current customer and HR is able to quickly and efficiently handle questions and concerns. The sales, marketing and strategy team also receive information form the CRM dashboard to attract new customers.
Cheyanne Kostaras-Nesbitt says
HI Georgios!
I really liked how you brought the CRM and ERP systems back and showed the connection to supply chain management, really tying those ideas together. Supply chain management is extremely fragile, and you showed why it is important in great detail.
Jenna Oldroyd says
Hi Georgios,
Great explanation of supply chain management! I agree with you; it is an excellent example of connecting back to ERP and CRM, as these systems can help manage and run an organization’s entire supply chain management process.
Rachel Bard says
I liked your sentence about a company before being profitable, they need customers and then relating it back to the importance of CRM systems.
Cheyanne Kostaras-Nesbitt says
Supply chain management is a very delicate system in business where raw materials are converted to sellable goods and sold to consumers. Supply chain management incudes every function in the process from sourcing raw materials until delivery. It is very fragile because it has so many moving parts that all rely heavily on each other. A mess up in one stage of production can cause a domino effect in the entire process, and therefore must be properly managed.
Cheyanne Kostaras-Nesbitt says
*Edited Post
Supply chain management is a very delicate system in business where raw materials are converted to sellable goods and sold to consumers. Supply chain management includes every function in the process from sourcing raw materials until delivery. It is very fragile because it has so many moving parts that all rely heavily on each other. A mess up in one stage of production can cause a domino effect in the entire process, and therefore must be properly managed. An example of this would be an owner of a small bakery assessing her orders for the month as well as what she wants to sell out of her case. She would then need to order the raw materials (flour, sugar, salt, etc.) She would then need to receive the materials, turn them into baked goods, and complete the sale. The final step in this scenario is to receive payment for the finished product. A delay in her assessment of her needs would cause a domino effect and delay every step, down to the last step of receiving payment.
Max Smith says
Why do companies use big data?
Many businesses use big data to optimize multiple areas of their business. Big data allows for better customer insights which aids a business’s sales and marketing. In addition, big data increases market intelligence, aids smarter recommendations and audience targeting, and makes data driven innovation possible.
Samir Lagouit says
Hi Max,
I think it’s important that you mentioned how big data allows for better customer insights. It really is as simple as the more information you can collect and have about consumers, the better prepared you can be. This in turn leads to a better customer experience(in a relevant industry), and is why big data is so much more valuable.
Mahbuba Ahmed says
What is business intelligence, and how does it help companies?
Business intelligence involves the use of tools and technology to collect, analyze and present business data for informed decision making. It helps companies by providing insights into their operations, customer behavior, and market trends. Business intelligence tools organize and present data in a user friendly manner, enabling executives and managers to make informed decisions based on accurate information. It aids in identifying patterns, trends, and areas for improvement, ultimately supporting strategic planning and performance optimization. In essence, business intelligence helps companies by turning raw data into meaningful insights, fostering better decision making across various aspects of the business.
Briana Seidle says
Hi Mahbuba,
Thank you for provided a clear, yet detailed explanation of business intelligence and how it helps companies. While I understand the purpose of business intelligence, I didn’t realize all it truly does.
Maurice Chism says
What is RFID, and how does it help supply chain management?
RFID it the ability to track the movement of your product through the state of inception through comp[etion. My example would be working on an assembly line like a car maker and the cars through their process on the assembly line. This allows the auto maker to view the processes that work and where there are potential hang ups within the process.
Elena Grigoryan says
Veracity of data means the quality and credibility of data. It is crucial to data integrity because you want your data to represent actual facts. Many decisions are drawn based on information available, so you need that information to be truthful and reliable. Incorrect, false information or misrepresented facts can lead to lower profits and damaged reputation.
Velocity of data refers to the speed at which data is collected and distributed. Data velocity is also an important aspect of data integrity. Things can change very quickly in business operations. Imagine if raw materials doubled in price, a business would want to know about such drastic change so service prices could be adjusted accordingly. Another example is hot leads. In a sales business, getting and following up on a hot lead is more productive if done sooner rather than later.
Briana Seidle says
Why do companies use big data?
Big data has transformed how companies operate and make decisions across every industry. They use big data to innovate and acquire a competitive advantage. This includes using big data to optimize inventory management by forecasting demand, and analyzing past and current data to avoid possible overstocking and stockouts. Companies also use big data to follow market trends, customer preferences, and competitor statistics. They can do this by analyzing data generated in social media platforms, customer reviews, and online forums.
Cristina Valentin says
Hi Briana,
I agree with your response, companies can use this data to their advantage. There is also so much data readily available, it would be a waste not to use it.
Lesly Puma Vinansaca says
Hi Briana
Your explanation of big data has helped me gain a bigger insight on how useful tool it is. I agree with how it helps companies gain a competitive advantage.
Jenna Oldroyd says
What is supply chain management, and how does it affect businesses?
Supply chain management (SCM) is managing the flow of raw materials and goods that are turned into a product from the beginning to the end. The supply chain management process involves many aspects of business operations, such as finances, purchasing, logistics, delivery, customer experience, and profitability.
Supply chain management can affect businesses through the supply and demand of materials and customers. It allows manufacturers to make, market, and deliver a product for the best customer satisfaction at the lowest cost and risk of doing business as possible.
Cristina Valentin says
What is supply chain management and how does it affect businesses?
Supply chain management is the process in which a product goes from being manufactured and ending up with the customer. It is important for all of the parts of this system to work in the most efficient way so that the company can get their products made, shipped and delivered to customers in a way that will be profitable. There also has to be careful consideration of the amount of product and the way products are shipped in order to optimize profits.
Hamida Akther says
Hi Christina,
I think you provided a very clear and simple explanation of supply chain management and how it affect businesses. It is very easy to understand and I really like the explanation.
Ereny Abousaif says
Hey crstina, Excellent supply chain management explanation! As these tools may assist in managing and executing an organization’s complete supply chain management process, I agree that this is a great example of integrating back to ERP and CRM.
Hamida Akther says
What is RFID, and how does it help supply chain management?
RFID stands for Radio Frequency Identification, which is a wireless technology. RFID uses radio-frequency waves to transfer data between a reader and a movable item to identify, categorize, and track. It identifies objects that have been fitted with special RF identification tags. RFID helps the supply chain management because it allows companies to track their supply chain workflow, and provide more usable data with manufacturing equipment which helps the inventory accuracy. RFID works by an antenna that reads electromagnetic energy, and can penetrate non-metallic solid objects. Radio Frequency Identification tags have more information than barcodes. The tags are programmable which is why scanning can be done from greater distance. Passive tags are inexpensive, and can range from a few feet. Also, the active tags are more expensive and list a longer range.The generated data can help streamline the areas of the supply chain through automation which can save time, and money. RFID helps the supply chain management in improving data accuracy and manages inventory which increases revenues.
Dana Persaud says
What is RFID?
RFID is Radio Frequency Identification. For supply chain management, it’s an easy way to track inventory, A RFID tag has the inventory items specific information and can be read with an antenna with electromagnet. The tags are programmable and can be scanned from a distance. Taking inventory isn’t a tedious task and can be done easily without lifting a finger. Many stores have started to use RFID tags for instore checkout use. Stores like Uniqlo use them as self-checkout and make it easy to find an item for a customer.
Samir Lagouit says
What is business intelligence, and how does it help companies?
Business intelligence is essentially a combination of strategies to achieve data analysis goals. An example is Powerbi a powerful tool that companies and individuals use to make decisions. With it, users can easily make visually appealing reports, dashboards, and charts, turning raw data into a something easily digestible. This visual representation is crucial, aiding users in troubleshooting and problem-solving for various issues by providing a clear picture of what they’re dealing with. Something companies couldn’t do 50 years ago, on just a simple application.
Business intelligence is a guide for users and more importantly businesses. It gives them the ability to navigate through complex datasets, to find hidden trends and patterns. BI tools like PowerBI deliver live analytics, allowing organizations to act quickly based on insights.
Lesly Puma Vinansaca says
Hi Samir
This was a great explanation of business intelligence. I enjoyed how you provide an example such as PowerBI to further explain how this is a useful tool for businesses.
Jorgelina Rodriguez says
great explanation! i agree with you 100%
Ereny Abousaif says
What separates data from big data?
The main differences between data and big data are the amount, speed, kind, and complexity of the information. Big data is the term for extremely large and diversified sets of information that are more than the capacity of conventional data processing techniques. Traditional data, on the other hand, refers to organized and manageable datasets that are easily processed by conventional databases. Massive amounts of data produced quickly from a variety of sources, such as social media, sensors, and transaction records, are combined to form big data. Big data is also distinguished by its diversity, which includes unstructured, semi-structured, and structured data kinds. Big data is complex because it requires analysis and the extraction of valuable insights from a variety of data sources and formats. Big data technologies have emerged, including sophisticated analytics tools and distributed computing frameworks.
Lesly Puma Vinansaca says
Descriptive analytics and predictive analytics are two key components of data analysis used in various fields such as business, healthcare, finance, and many others. Descriptive analytics helps in understanding past events and current trends. It focuses on summarizing and presenting data in a meaningful way to gain insights into patterns, trends, and relationships within the data. While predictive analytics focuses on forecasting future outcomes based on historical data and statistical models. It involves the use of advanced techniques and machine learning algorithms to analyze past patterns and trends in data and make predictions about future events or behaviors. Both types of analytics play crucial roles in data-driven decision-making and business strategy formulation.
Erica Griggs says
Good Job Lesley nice discussion post as usual! You brought up some great points.
Hadeer Saad says
What are the differences between OLTP vs. OLAP, and what are some examples of each?
The difference between OLTP vs. OLAP is, that OLTP is used for real-time processing, while OLAP is used for complex data analysis. They are 2 important data processing systems often used in data science. Also, OLAP does online analytical processing, and OLTP does online transactional processing.
Examples:
We use OLTP data systems in a variety of industries (ATMs, online banking, online bookings, ticketing, and reservations), and they are in many consumer-facing systems.
We use OLAP to combine and group data into categories. For example, Amazon stores data about the products it sells, such as kitchenware, baby gear, and outdoor furniture etc.
Lancelot Nyandoro says
Yes, Hadeer. OLTP focuses on individual transactions between a computer system and one person. And OLAP helps companies process data. for the performance within a company
Erica Griggs says
Good job Hadeer! You did a whole breakdown of the differences in OLTP vs. OLAP!
Erica Griggs says
“Why Companies Use Big Data”
In our MIS class, we’re talking about why companies use Big Data. Simply put, it’s like having a super smart assistant for businesses. Imagine you own a store. Big Data helps you understand what customers like, when they shop, and how much they spend!
Companies want this info to make better decisions. It’s not just about selling more stuff! it’s also about solving problems, and saving money. Like, if a company sees people prefer chocolate ice cream, they’ll stock more of that.
So, Big Data is like a toolbox for businesses. It helps them figure out what works, what doesn’t, and how to make things better. It’s not about excitement, it’s about being smart in business decisions. That’s why companies are all into Big Data these days.
Mairaliz Negron says
What is business intelligence, and how does it help companies?
Business Intelligence (BI) analyzes data into actionable insights to help make informed decisions. This is a powerful and useful tool in the business world. Companies are able to determine and see what it is that they’re doing right and/or what areas need improvement. It helps to manage your company in staying ahead of your competition. Overall, this tool is a great way to make your business/ company strong and successful.
Eduard Lagutin says
Hey Mairaliz,
I like your description about business intelligence and the provided example of how it helps companies.
Great job!
Eduard Lagutin says
What separates data from big data?
Information becomes “big data” when it’s too much for normal systems to handle well. The difference is in how much data there is, how fast it comes, how many kinds there are, and how trustworthy it is. Big data includes huge amounts of well-organized and random data from many places like social media, sensors, and business deals. It covers lots of data types, like words, pictures, and movies, needing really good ways to get useful stuff out of it. Also, big data often has problems with how good and sure the data is. The thing is the size, the mess, and the speed of big data, needing special tools like split up working, smart machines, and info digging to get good ideas and smart choices from all this data.
Daniel Taylor says
This was a good respond to read and to help me understand more of what big data is compare to data. I always thought of these two to be the same just with big data being more complex reporting.
Rachel Bard says
What are the sources of data?
After completing the the the AI LinkedIn Training, it really opened my eyes to the collection of data, The instructor was basically saying the apple watch is tracking what your doing so it can add to the hidden aspects of AI, The tracking helps identifying K-neighbors and getting conclusions from inputs. The amount of data collected for AI to become more self reliant is insane. I also think we all forget how much of our data is being collected. Our smart phones, the websites we visits, the products added to our wishlists. All these tasks are all being tracked and stored somewhere, partially so AI can be given more information to come to more realistic/ and conclude with more human outcomes. I think the sources of data has blown my mind more during taking this course than anything else in my life. Even when I went to Disney last year, I didn’t think of the Magic Bands as tracking me, but an easier way to move about the park.
Leanna Paul says
Hi Rachel, you made good points about the way AI is almost everywhere now. The apple watch is definitely collecting data as it already is tracking things such as your steps and heart beat. The magic bands at Disney is a great example. Good post!
Leanna Paul says
The key differences between traditional data and big data are related to volume, variety, velocity, complexity, and the potential value of the data. Traditional data is typically small in size and structure while big data is large, complex and constantly changing. Big data uses a dynamic schema that includes both structured and unstructured data.
Hawa Barry says
Hi Leana,
This is a nice, simple explanation that differentiates traditional and big data, and I like the use of “schema”.
Jorgelina Rodriguez says
huge data is used by businesses to extract insightful information from large, diversified datasets that are too huge for conventional data processing techniques to handle effectively. Businesses can find patterns, trends, and correlations in big data that aid in making well-informed decisions. Big data helps businesses gain a deeper understanding of consumer behavior, which improves targeting and allows for more individualized marketing plans. Additionally, it provides predictive analytics, which enables businesses to foresee market trends, spot possible hazards, and proactively enhance operations. In the end, big data use boosts growth, innovation, and competitiveness in today’s data-driven business environment.
Corey Reagan says
What is RFID, and how does it help supply chain management?
RFID, which stands for Radio Frequency Identification, is a technology used for the identification and tracking of objects using radio waves. It is a wireless communication technology that allows data to be transmitted and received between a tag, also known as an RFID tag, and a reader. It has revolutionized supply chain management by providing real-time observation and accurate inventory tracking. This technology enables businesses to streamline operations, optimize inventory levels, prevent stockouts, and enhance customer satisfaction. By facilitating seamless communication between suppliers, manufacturers, distributors, and retailers, Its ability to read multiple tags simultaneously, track individual items in real-time, store and transmit a large amount of data, withstand harsh environmental conditions, and promote automation makes it indispensable. Another benefit of RFID in supply chain management is enhanced traceability and transparency. By tagging products with RFID labels, companies can easily track the movement of goods from manufacturing to distribution to retail. This visibility allows for better coordination of logistics, improved demand forecasting, and faster response to changes in market demand or disruptions in the supply chain. As more companies adopt RFID technology, we can expect to see continued advancements in supply chain management and greater value creation across industries.
Dylan Milano says
Hi Corey,
Your explanation of RFID technology and its impact on supply chain management is thorough and insightful. RFID technology indeed plays a crucial role in enhancing efficiency and visibility within supply chains. I like that you highlighted key benefits such as real-time tracking, accurate inventory management, and improved traceability.
Dylan Milano says
Descriptive analytics involves understanding historical data to comprehend what has happened in the past. By summarizing key information and trends, descriptive analytics offers insights into past performance and helps organizations comprehend their current state. On the other hand, predictive analytics leverages historical data, statistical algorithms, and machine learning techniques to forecast future outcomes. By detecting patterns and trends, predictive analytics enables businesses to make informed decisions proactively and anticipate potential scenarios. Both descriptive and predictive analytics play pivotal roles in data-driven decision-making, with descriptive analytics providing context and predictive analytics offering foresight for strategic planning.
Big data refers to vast and complex datasets that conventional data processing tools are inadequate to handle efficiently. Companies utilize big data for various purposes, including analyzing customer behavior, gaining market insights, improving operations, and enhancing decision-making processes. Business intelligence refers to technologies, applications, and practices for gathering, integrating, analyzing, and presenting business information. BI tools provide organizations with actionable insights, visualizations, and reports to support strategic decision-making. By leveraging big data and business intelligence tools, companies can extract valuable insights, identify trends, and optimize business processes for competitive advantage in a data-driven landscape.
Kerri McGuckin says
Hi Dylan,
I agree the descriptive and predictive analytics are both important parts of data-decision making processes. I think both types of analytics would go hand in hand in most work places as most data analysts are looking at past and current data and trying to come up with work flows for the future.
Hadeer Saad says
What are the differences between OLTP and OLAP, and what are some examples?
OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) are two different types of database systems designed to serve distinct purposes within organizations.
OLTP systems are optimized for transactional workloads, focusing on efficient and rapid processing of day-to-day transactions such as sales, orders, and inventory updates. These systems are characterized by their ability to handle a high volume of short, atomic transactions in real time. OLTP databases typically have a normalized schema, emphasizing data integrity and minimizing redundancy to ensure efficient transaction processing. Examples of OLTP systems include retail point-of-sale systems, banking transaction systems, and airline reservation systems.
On the other hand, OLAP systems are designed for analytical workloads, enabling complex querying, reporting, and data analysis to support decision-making processes. These systems are optimized for retrieving and aggregating large volumes of historical data from multiple sources to generate insights and support strategic decision-making. OLAP databases often use a denormalized schema and multidimensional data models to facilitate complex queries and data analysis. Examples of OLAP systems include business intelligence (BI) platforms, data warehouses, and executive dashboards.
In summary, the main differences between OLTP and OLAP lie in their purpose, design, and usage. OLTP systems focus on transaction processing in real time, while OLAP systems support analytical processing for decision-making and reporting purposes.
Hadeer Saad says
RFID (Radio Frequency Identification) is a technology that uses radio waves to identify and track objects remotely. It consists of tiny RFID tags containing electronic chips and antennas and RFID readers or scanners emitting radio waves to communicate with the tags and retrieve information stored on them. RFID tags can be attached to various items, such as products, containers, or assets, enabling them to be tracked and monitored throughout the supply chain.
RFID helps supply chain management in several ways:
1. **Inventory Visibility**: RFID enables real-time inventory tracking and monitoring as it moves through the supply chain. By automatically capturing data about the location, status, and movement of goods, RFID improves visibility and accuracy in inventory management, reducing stockouts, overstocking, and shrinkage.
2. **Efficient Logistics**: RFID streamlines logistics operations by automating processes such as receiving, picking, packing, and shipping. It enables faster and more accurate identification of goods, reduces manual handling and paperwork, and improves warehouse operations and transportation management efficiency.
3. **Enhanced Traceability**: RFID provides granular traceability by capturing detailed information about each product’s journey from production to consumption. This enables organizations to trace the origin of products, comply with regulatory requirements, and respond quickly to recalls or quality issues.
4. **Supply Chain Optimization**: RFID data can be integrated with other supply chain systems, such as inventory management, warehouse management, and enterprise resource planning (ERP) systems, to enable better decision-making and optimization of supply chain processes. By leveraging real-time data insights, organizations can improve resource allocation, reduce costs, and enhance overall supply chain performance.
RFID technology plays a crucial role in modern supply chain management by improving visibility, efficiency, traceability, and optimization throughout the entire supply chain ecosystem.
Kerri McGuckin says
Data visualization is the process of visually describing data so that is is easier to understand. Some of these visualizations can include graphs, charts, maps… etc. This process can be used in many different fields to represent data.
Data Analytics is the process of examining the data and identifying patterns and relationships in the data. This can also be used in a variety of fields such as business, science, and healthcare. The healthcare company that I work for has many data analysts working for us that try to improve most of our processes by examining our current data.
The main difference between data visualization and data analytics is that visualization is only used to show people the current data and organize it so it’s easier to read. Data Analytics is actually taking the current data and trying to draw insight from it or predict future trends.
-The main difference between data and big data is the amount of data involved in each. Big data includes very large amounts of data that cannot easily be processed with traditional database systems. A lot of companies use big data to get the most information as possible so that they can optimize user experience or help with product development. Data Analysts could possibly work with information found from big data as part of their roles.
Hawa Barry says
Big Data characteristics include volume, velocity, variety, veracity, value, and variability. To define each term, volume refers to the size of data being handled in enormous amounts. I’ve never heard of an Exabyte, but if the global mobile data per month was 6.2 Exabytes in 2016, I can imagine that volume truly has to exceed normal amounts of data. Velocity is the high speed accumulation of data. Variety refers to the way data is structured, semi-structured, and unstructured. Structured data is organized, Semi-structured data is still organized, but it does not conform to formal structure of data, and Unstructured data is unorganized and can’t be placed into a traditional database. Unstructured data typically involve media such as texts, pictures, and videos. Veracity refers to inconsistencies and uncertainty in data. Value just assures that data is transferable to a numeric value of sorts, whether it’s measurable. Finally, Variability refers to how often does the structure of the data changing.
Daniel Taylor says
What are descriptive and predictive analytics?
Descriptive analytics is when reporting financial metrics such as a year-on-year change in pricing, monthly sales growth (or decline) figures, and revenue from subscribers. Then for predictive analytics is when models may be able to identify correlations between sensor readings. For example, if the temperature reading on a machine correlates to the length of time it runs on high power, those two combined readings may put the machine at risk of downtime.
Dana Persaud says
What is RFID?
RFID stands for Radio Frequency Identification.Radio Frequency Identification specifically aids in managment in supply chain. Radio Frequency Identification is an easy way to track inventory. A Radio Frequency Identification tag has the inventory items specific information and can be read with an antenna with electromagnet. The tags are programmable and can be scanned from a distance. Taking inventory is usually a tedious task and can not be done without hours of manually counting inventory. But with a Radio Frequency Identification and can be done easily without lifting a finger. Many stores have started to use Radio Frequency Identification tags for instore checkout use. Stores like Uniqlo use them as self-checkout. At checkout the customers will simply place the items in a bin, the item will can automatically, and the customer will proceed to payment. Additionally, if an item is not in the front of house the workers can track the item from the RFID tag and make it easy to find an item for a customer.