What is the Benefit of Modern Data Warehousing?

[Guest Post by Ronald van Loon]

Access to relevant customer and industry information is the primary competitive advantage businesses have over their direct and indirect competitors today. It is the smartest approach to remaining vigilant in a business environment where competition is at an all-time high.

That is where data warehousing comes in. Data warehouses are central repositories of integrated data from one or more disparate sources used for reporting and data analysis, which—in an enterprise environment—supports management’s decision-making process.

Digitalization is integrated into the foundations of today’s business landscape, and there is no going back from here. Software companies are improving data engineering algorithms, and data analytics providers are using advanced techniques to provide better solutions to businesses. The result is much more efficient business intelligence solutions.

Businesses who are new to this trend and are skeptical about the availability of the data often inquire, “why do we need data warehousing systems?”

Data is Power

The simple answer is because data is knowledge and knowledge is power. A business with relevant information and access to useful industry insights has a greater chance of successfully striving in the business landscape and dominating the niche.

Access to Data Minimizes Risks

Entrepreneurs know that there is always some kind of risk involved when it comes to business processes. Although entrepreneurs are risk takers by nature, the smaller the chance of risk, the better. This is probably the most convincing reason for businesses to invest in data warehousing solutions.

Accurate data about your customers and the state of the industry minimizes uncertainty because it helps you make better decisions with definite outcomes. With the right kind of data, you can analyze past trends and forecast future outcomes with a high probability of accurate results.

For example, in IT operations, Distributed Denial of Service (DDoS) attacks are increasingly becoming common. To ward off such attacks, having a centralized logging architecture to identify suspicious activities and pinpoint the potential threats from thousands of entries is essential.

Another example is the core objective of a healthcare facility is to cater to the needs of patients. Data analytics has not only proven to be beneficial for the mundane tasks related to administration but also to have a positive impact on a patient’s overall experience. By maintaining a database of patients’ records and medical histories, a hospital facility can cut down the cost of unnecessary, repetitive processes.

Apparel industry is a third example that benefits from the access of data. The data enables companies to better cater to the needs of the public. With an idea of what the masses require, fashion industry thrives and rarely misses.

What’s Next for Data Warehousing Systems?

Big data analytics is a fast-paced industry that keeps on improving and evolving. There is no constant state in this industry, and that is why Business Intelligence (BI) should continuously evolve at the same pace.

BI is one of the determining factors shaping the future of data warehousing, data mining, and data engineering.

Why is there a need for continuous changes? The simple answer is that older BI processes cannot keep up with the customers’ demand. They lack in their ability to accurately interpret and quantify business’ Key Performance Indicators (KPIs) and Return on Investment (ROI).

A data management system is useless if it cannot fulfill its primary purpose of predicting accurate information about business processes.

In addition to that, older BI systems are also ineffective ways to integrate information from multiple channels and streamline the communication between various departments.

Big data companies are trying to improve data warehousing solutions in order to meet the new set of requirements. The modern data warehousing structure can store data in its raw form instead of the previously opted hierarchical structure. This enables users to more easily access data.

New data warehousing solutions also minimize the inefficiencies caused by gaps in communication. State-of-the-art structures can integrate the information from multiple channels and store it on one platform, streamlining the communication process.

The biggest recent advancement that we’ve seen in data engineering structures is that data analytics software has become extremely user-friendly. Previously, only professionals with the appropriate skill set were able to work with data. Now anyone with basic information can deduce results and information because the complex aspects of data engineering are taken care of by computer algorithms.

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Ronald van Loon is an Advisory Board Member and Big Data & Analytics course advisor for Simplilearn. He contributes his expertise towards the rapid growth of Simplilearn’s popular Big Data & Analytics category.

If you would like to read more from Ronald van Loon on the possibilities of Big Data and the Internet of Things (IoT), please click “Follow” and connect on LinkedIn and Twitter.

This article first appeared here. Used by permission. 

Forget Fake News – Here Comes Fake Data

AI voice assistants will cause a flood of fake data

Everyone and their grandma are now working on algorithms to fact-check news. But as manufacturers, marketers and especially as consumers, we are facing a much bigger enemy. It is called artificial intelligence.

This is the present: you run out of milk and go to the store. Or you go online to order. Soon Alexa – Amazon’s AI solution will enter your home, or whatever other systems you choose. Everyone seems to be working on one. Like it or not, Voice AI will be the interface of the future. (Incidentally, why are all sinister AI systems female? Because of the Adam and Eve story? Note to self: ask an anthropologist.)

Now, once you got your new girlfriend up and running and you realize you are out of milk, you can say “Alexa, order milk!” Alexa will perhaps say “which brand?” You could answer “Are there any special offers?” And Alexa will say “at XYZ supermarket, TastesTerrible is having a 2-for-1 sale.” Having never heard of it, you will say “TastesTerrible? Is that a good brand?” And here is where the real kerfuffle begins.

With AI we will rely on automated voice systems to make our purchase decisions, but the AI is based on existing digital information. And that information can be manipulated. How will “TastesTerrible” end up being recommended by Alexa? Either by the number of likes its Facebook page has, or a ‘scientific’ study showing it is the best milk in the world. Or some marketer posting about TastesTerrible in a random foodie forum.

Take this real-life example. Ask Google Home (or simply google on the web) “What is the best motherboard brand?” The answer you will get is this:

“ASUS, MSI and Gigabyte are the 3 best motherboard makers, saying that one or the other are better is personal preference. By its very nature AsRock cannot be the best motherboard brand since its ASUS’s lower end brand, but since it is a derivative of ASUS it does have very good boards, often at very good prices.”

This is a completely arbitrary answer from a September 12, 2010, post on Tom’s Hardware. It is outdated and factually wrong (ASRock is an independent company, and its motherboards often rank better than the other three brands). (Disclosure: ASRock is my client.)

Whether you agree with that statement is beside the point. However you look at it, we are entering the age of marketing through Voice AI. How, as marketers, do we get any product message across, if artificial intelligence systems will repeat any nonsense they find on the net.

 

Voice Marketing Concentrates All on the Winner

Product marketing is becoming be a matter of manipulated data. And no one will get a grip on it initially. Big brands will spend billions in creating data to monopolize the AI systems. Your product, dear startup, not having the clout or money to produce that data, will remain invisible. No amount of Facebook or Google ads will change that. Marketers will ultimately become obsolete. Data manipulators will take their jobs. Hashtag #jobsforthefuture.

Well we are not there yet. But don’t underestimate the impact of artificial intelligence on the marketing business in the long term. Siri & co will soon be everywhere. There are companies working on bringing these AI systems to every corner of your life. You thought SEO was a hassle? Try doing SEO for Alexa.

The reason why AI is such a problem is that it’s not AI at all. There is nothing artificial about the intelligence Google, IBM, Apple and Amazon are peddling. It’s human-sourced intelligence. The misleading post above came from a misinformed human being. Just because Alexa says it doesn’t make it “artificial” or authoritative.

So, when Alexa and her girlfriends recommend a product, they are relying on human sources. Manipulating these sources, in other words “AI-SEO” will be the fastest growing business in the coming years. The crux of the matter is, you can create product comparison studies that prove anything. Just think of clinical studies: the ones that are beneficial to pharma companies are published, the rest is buried. AI based on such skewed data will never be authoritative. Or the organic vs. GMO debate. Who will win the data war – green bloggers or big food brands?

As AI rises, we seem to be destined to drown in fake data. Sooner or later we will come up with fact-checking algorithms for news and data. But that could take some time. And even if we do, nothing in marketing is really objective, as we know. The brands that control the data will control the world.

Enough doom and gloom. Here is the silver lining. Even without fact-checking, the more data in the AI system the more objective it will become. Algorithms will improve gradually to weed out the worst offenders. But it will be a painful transition, and for decades to come, brands will fight over data and how to put the right words into Alexa’s mouth.

Read also: Opportunities Created by AI Outweigh Imminent Threats

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