Tag: Big Data

4 Major Misconceptions about The Cloud

Posted on June 11, 2015 by Doug Hoogervorst - Blog, Uncategorized

The rise of cloud technology, applications and its other components have totally flipped the technology industry on its head. Businesses and individuals have both benefited from the cloud’s ability to store their data wirelessly and in a way that is accessible from any location with wireless internet capability. And as it becomes more ubiquitous, more companies are looking to implement a cloud IT infrastructure to gain a competitive advantage over their rivals.

And cloud technology has definitely given some business owners the advantage by being able to utilize a more agile infrastructure that not only saves space, but creates more opportunity for where and how work is done. On the flip side, as many are making use of this new age resource, some are still left in the dust and fail to fully comprehend the mechanics of the technology.

That’s why we’ve broken down the most common misconceptions to clear up some of the characteristics that cloud technology can offer you.

It’s Less Safe Than Other Methods

The literal imagery of a cloud storing your information makes it easy to assume that it’s in a vulnerable location that can easily be accessed. However, this is not the case. In fact, according to Gartner, more security breaches take place in on-premises data center environments.

Cloud storage areas are easily tempting as they store the information of several organizations, but additional security measures like encryption serve as an extra layer that prohibits access even when a cloud center’s security is compromised.

Once You Switch, It’s for the Entire Company

Another common misconception is that once a business decides to switch to cloud computing or storage, that is also applies to every possible area of the company as well. And that’s not necessarily the case. It’s absolutely depends on your company’s unique needs, current infrastructure and capacity.

It’s imperative to weight your options and list out the benefits of both cloud and non-cloud technology. For some processes or areas of your business, having an on-site solution may work best. To maximize your efficiency, many businesses are employing a hybrid structure where different vendors handle different tasks. Whatever works best for your business should be the top priority as a uniform platform may not be perfect.

It Will Cost More Than On-Site Storage

This is also not necessarily the case. Switching to cloud takes away the financial need to hire an IT team to manage the technical aspects of your business. And in the long run, the responsibility of managing your cloud computing is put in your hands and will save you in the long run. Of course, however, this depends on how you will use the cloud.

For example, if you decide to build apps to reduce the need to purchase new hardware, this can amount to more than if you stayed with your previous infrastructure.

Productivity Will Spike Automatically

Just because you’ve implemented a new cloud structure doesn’t mean not much work is needed to see results. While some companies build applications that are hosted on the cloud, it can be a huge benefit to spend time figuring out how it can be best used. Combining both cloud and local storage to host your app is suggested to give you some flexibility and redundancy when using the app. It can certainly help productivity, but don’t bank on the cloud technology to do all the work for you.

In summary, making the switch to cloud, especially for your business intelligence needs, has the potential to greatly improve and simplify the way your company operates. With the use of a specialist to guide you through the process and an eager team that’s ready to maximize their performance, the possibilities for growth and productivity are endless — if implemented the right way, of course.

Don’t allow these misconceptions hinder you from exploring new options, but rather, let them guide you in making the right choice for your business, employees and customers.

4 BI Improvements You’ve Been Waiting For

Posted on June 8, 2015 by Doug Hoogervorst - Big Data, Blog, General

As we have successfully made it past the midpoint of 2015, the year is shaping up to offer several new enhancements in big data and analytics. Much of the improvements that come in the BI community comes in the form of either simpler, faster or more — and this improvement trickles down to businesses of all sizes across the globe.

This is why it’s exciting to see what new trends will emerge, what traditional strategies will be flipped on its head and who will be the pioneers in implementing these new improvements. Here, we’ll break down four major changes that are soon coming our way in the BI community and how to implement these strategies within your system to benefit your growing business.

Datafication

Datafication is what you get when you’re able to display, track and analyze individual processes with your technology. While this isn’t necessarily revolutionary in terms of business intelligence, datafication is picking up steam with more real-time capabilities being used and valued.

A perfect example of this technology is Fitbit, the wireless, wearable activity tracker that “measures data such as the number of steps walked, quality of sleep and other personal metrics.”

It’s datafication that makes this information visible all of a sudden via a device that’s made to specifically designed to display it. This data goes a long way in tracking movements and monitoring health concerns for those trying to lose weight, stay fit or simply desire to monitor their personal health.

And this is just the base level. Datafication opens the doors for businesses to optimize tracking. The use of sensors, real-time technology and a full-fledged analytical display can serve as a tool that businesses can use to monitor their own processes with ease.

Community

Long gone are the days were one person would control all the analytics capabilities. Instead, we’ve evolved to the point where IT spending has become more of a collaborative effort where each analyst’s input should be valued and respected as there can be several paths to a solution.

Analytic organizations are coming to a point where community is in charge, not the individual. With scattered sources, educational backgrounds and data perspectives, this means data teams will need to implement internal social networks where collaboration is the more effective method of data analysis, as opposed to disparate ideas taking longer to come together.

Analytics Ecosystems

One of the first steps in establishing a comprehensive big data infrastructure entails using the varying inter-dependencies of your company and synchronizing them. Viewing your company’s BI solutions as an ecosystem goes a long way in collaborative efforts to make use of the big data that you collect.

Take it from IBM Data Magazine:

“A successful big data analytics program requires many interacting elements … data, which has to be integrated from many sources, different types of analysis and skills to generate insights and active stakeholders who need to collaborate effectively to act on insights generated.”

As a “network of interconnected and interdependent entities,” having a well-defined ecosystem helps to alleviate the path of big data while making it useful for every element of the system. There are three interacting spheres that define the analytic ecosystem including the core, extended and external.

Data Privacy

The subject of data privacy, while evolving, is still trailing the evolution of our technology. With the necessary involvement of governments and politicians, it’s likely that the laws that need to be stringent will become so far after they’re initially needed.

The private sector also has a responsibility in maintaining transparency with their customers and partners as to where their information is being stored and if it’s being distributed to a third-party.

As more conversations are had surrounding the subject, the coming years should offer more solutions that protect consumers while holding companies and governments accountable for their actions.

Data Privacy: What’s the Big Deal?

Posted on June 4, 2015 by Doug Hoogervorst - Big Data, Blog, General

For those in the private sector, collecting customer information serves as an incredible tool to not only engage with your customers, but to also cater to their needs. The amount of information that prospects are willing to give you also allows you to gauge their interest in your services.

However, while your website may be a primary source where clients and prospects share their information, many are questioning the actual use of this information.

Is it really being used to just send company emails or could their personal information end up in the hands of a third-party?

Data privacy is a growing concern for those on the receiving end of businesses who make use of big data tools. While collecting data is ultimately voluntary for prospects and consumers, where it goes after it is given is the main concern. And who should be in charge of maintaining the order?

It’s clear that businesses shouldn’t be the ones in charge of maintaining the ethical order as the conflict of interest is clear — which means the responsibility can only be left in the hands of our government.

Data Privacy & The Government

When Edward Snowden revealed the telecommunication spying efforts done by the NSA on millions of American Verizon customers, it sparked the conversation surrounding the question of how secure is our information really?

Both the White House and the Federal Trade Commission have addressed the topics and are striving to make more stringent policies in protecting big data, but the topic still remains unsettled. But perhaps it shouldn’t be unexpected that the issue is ongoing. It’s especially difficult to monitor big data privacy concerns when the entity that is supposed to establish and maintain judicial law is overstepping its boundaries by wiretapping its own citizens.

Areas of Improvement

When you download a new application for your phone or new program for your desktop, you’ll likely have a Terms & Conditions page that requires your approval in order for you to use the new software. Companies often use heavy-loaded jargon to discourage users from reading the script entirely and it’s here where their attempt to be transparent smoothly slips the mind of the user.

As a business who is likely collecting big data, it’s advised to be as transparent as possible — without the lengthy distractions. Keeping your customers and prospects in the loop of where their personal information is going is key to building a solid relationship as the question will likely come up if your customers are aware of the growing concern of data privacy.

Data Brokers

The companies that purchase consumer information and analyze their purchasing behavior are known as data brokers. Once they’ve collected this information, they sell what they’ve gathered to companies who are looking to maximize their marketing.

While the consumer may or may not have signed off on this use of their data, their information is still out there being used.

Steps to Tighten Up Your Data Security

Make sure your cloud technology is up to par. This should be one of your first steps in protecting your most important big data.

As these cloud storage initiatives are affordable and flexible, it serves as the perfect medium to house your customer/prospect information. While great, it still has its limitations.

Keeping your information safe from intruders is necessary as the information is likely stored in a public server, where it’s easier for intruders to infiltrate. Moving to a public cloud source gives you an extra layer of security where data is kept safe and visible to only you and whoever you assign responsibility to.

Another measure one could take is to sanitize your data. According to a data warehouse specialist from Emory University, Amy Dean says, “apply filtering, cleansing, pruning, conforming, matching, joining and diagnosing at the earliest touch points possible.” This relates more to the analytics portion of data storage and helps to ensure the quality of information that you’ve collected is correct and up to date.

Lastly, the most transparent way to ensure the ultimate data privacy is to allow your clients and even prospects to view the data you collected about them. Allow them to change information as they see fit — without making it a costly or difficult process. While this may seem unlikely for any company to do, in terms of transparency, it is the most fair.

IoT — Is it the Next Digital Revolution?

Posted on June 1, 2015 by Doug Hoogervorst - Big Data, Blog, General

There was once a time when the idea of having a device in your pocket that could make phone calls was unheard of. Then, there was a time when the Internet was just going to be a short-lived idea that only benefited scientists and researchers. Now today, everyone is waiting at the edge of their seats for the latest technological innovation — and more importantly — no idea is too far fetched anymore.

One of the latest major trends in technology that’s affecting businesses worldwide for the better is the Internet of Things (IoT). By combining the capabilities of billions of devices, IoT is changing the way data is collected and shared globally — simplifying the workload of workers and streamlining several processes.

What Exactly is IoT?

IoT is the connectivity among devices — computers, mobile phones, machines and practically any device with internet capability. It started with home automation, which was often used for a synchronized entertainment system or to maintain a safe kitchen with automated kitchen appliances that would respond to safety issues or cook recipes — all with less input from humans.

How Will it Shape the Future of Technology?

Now that the trend has been picked up and successfully applied to several industries, the concept has flourished and is only showing signs of growth. In fact, Gartner forecasts that “4.9 billion connected things will be in use in 2015, up 30 percent from 2014, and will reach 25 billion by 2020.”

Furthermore, the amount of revenue that the big data and technology sectors will generate will also be on the rise. According to a recent IDC report, “the big data technology and services market will grow to $41.5 billion through 2018 — six times the growth rate of the overall information technology market.”

A major part of IoT’s development that is often overlooked is where the true power really is. As many argue that it’s the devices themselves that offer this major growth, the more sound explanation is really based in the connectivity that IoT offers.

The technology is not only seamless, it has the potential to be global, maximize real-time data capabilities and offer humans a performance partner that doesn’t have to be put on the payroll.

In the same way that the Industrial Revolution paved the way for high-quality, life-simplifying innovation, IoT has often been compared to being able to accomplish the same things.

How the focus of the country shifted from farming to machinery, IoT has the potential to change the employment culture from manning machinery to clocking in at work on a device to oversee the machines work on their own.

Steps to Take to Maximize IoT

Investing in relevant technology and having an open mind serves as a great benefit should your organization care to get involved with the Internet of Things. With the proper implementation, use of trial and error and consulting with technology experts, your business stands to gain several positive effects, including:

– Higher quality service
– Increased production
– Streamlined maintenance requests
– More access to real-time data
– Quicker & better decision making
– Less physical work & more oversight duties

As a business who is likely trying to simplify their operations while implementing new technologies, making use of IoT is a trend that you do not want to neglect. Being left behind as the trend’s momentum pushes your industry forward is a spot where you do not want to be in as it may lead to you having to invest more time and energy later on.

Instead, consult a BI specialist or big data analyst who’s well aware of how implementing IoT’s features within your business can truly revolutionize your company for the better.

What Does “BI Solution” Really Mean?

Posted on May 29, 2015 by Doug Hoogervorst - Big Data, Blog, General

Have you ever been having a conversation with a consultant, but were unaware of the buzzwords that kept being brought up? Often times in the business intelligence industry, this is the case. However, we understand that an informed consumer is the best kind of customer and we would rather you have a firm understanding of your potential BI options than to be overwhelmed by keywords.

That’s why in this post we’re going to break down the popular terms that are frequented in BI circles. These terms are the ones that are more broadly considered BI solutions.

“Products”

In the BI community, the term product is arguably the most generic. It can refer to many things outside of a business intelligence context, but within its context, the definition is quite simple.

If you find yourself shopping for a tool to use to enhance the way your company gathers, tracks, displays and analyzes your data, you’ll find products on the sales floor that are dedicated to helping you accomplish your mission. While you may have found an answer to your professional need, you will likely need a professional BI consultant to help you integrate and implement the new product into your existing system.

“Solution Accelerators”

Solution accelerators are also known as blueprints. They are likely a collection of tools that have been used on prior projects. Project tools like data connectors, transformation logic, metrics, data models and dashboards are prime examples of a solution accelerator.

Instead of starting a project from the very beginning, these tools (for a lack of a better term) accelerate the overall process of using business intelligence to your full potential.

“Architecture”

The architecture of a BI system deals with the framework that organizes the data. Its role is crucial because it affects development and the decisions made in implementation. It includes data sources that users need to analyze their statistical information.

Depending on who you ask, structured or unstructured data is included in the makeup of BI architecture. This overall framework is customizable and can include applications like reporting, data mining, data visualization tools and more.

Before You Commit…

When you’re on the market searching for a new product, it’s super important to do your research beforehand so you’re not perplexed when the time comes to choose your BI solution. Knowing the difference between these keywords not only saves you time in the purchasing process, but it also gets you closer to understanding which solution will truly meet your company’s needs.

Whether you already know what you’re looking for or if you need guidance in making the right decision, feel free to contact one of our representatives. We’ll gladly assist you in clearing up any confusion you may have with understanding business intelligence and any of its tools.

Is Your Business Intelligence TOO Complex?

Posted on May 26, 2015 by Doug Hoogervorst - Big Data, Blog

A major part of maximizing your business intelligence solution is the ease in which you’re able to use it yourself. Of course, if you have an independent BI team that is managing all of your tools, then the need to understanding the inner workings of it decreases in importance.   However, for those of you who are taking on the responsibility, we understand how difficult it can be to learn on the job. New tools bring new stresses — and new terms bring on new confusions. And with constant changes coming in the industry, it raises the questions:

– Can BI become too complex in nature?
– How much is too much business intelligence?
– When do you know it’s time to simplify your tools?

In this post, we’ll highlight the tell-tale signs of an overcomplicated BI structure within your organization and offer ways to make sure your data collections efforts remain simple, intuitive and effective.

The Importance of Simplicity

“For BI to be actionable, it must be accessible,” says steven Schneider, Chief of Products at Logi Analtics.

And this couldn’t be more true. Not every business is large or fortunate enough to have the ability to train employees on how to use the several BI tools that are available. And while the technology may be affordable for an organization, the training and/or hiring of an in-house analytical team can cost more than organizations can handle.

After all, it’s important to note that the true value of business intelligence is NOT in having the tools — but in having the know-how to make smart decisions with the data gathered from these tools.

Simplification is Becoming a Trend

While some BI manufacturers are still creating tools that are geared towards highly-qualified data scientists, there is also an influx of data tools that cater to those who aren’t as well versed.

For business functions that are more widely used, such as modeling, profiling and algorithm blending, simpler versions are now becoming more commonplace in new BI solutions. Making these functions easier to use not only benefits the end-user, but also helps the BI provider’s sales by creating a wider audience for their product.

When Complexity Becomes an Issue

For a newcomer, dealing with company statistics is bound to be a challenge. One must deal with many graphs, statistics, charts, algorithms and more — and be able to interpret all of their meanings.

With that said, BI tools are supposed to lessen the gravity of this task by doing most of the grunt work for you. However, sometimes you may find yourself doing more work than you anticipated if your BI infrastructure is overly complicated.

Here are some signs that your BI solution is actually becoming more of a limitation rather than an asset to your organization.

– You find yourself asking more questions than solving issues
– More time is spent figuring out HOW, than actual work
– No progress is being made in speed of decision-making
– Analysis takes longer than pre-BI implementation

Looking Towards the Future

Besides the inevitable fact that business intelligence will become democratized even further as the years go by, one thing is true: more employees will be able to make use of BI tools as the technology becomes easier to use.

The need for highly-educated data scientists will also decrease. More organizations will be able to take full advantage of the many years of BI development to make better, faster and more long-lasting decisions as long as business intelligence continues to simplify.

And with all of these changes happening concurrently, the ones who adapt to these changes earlier, will also be the ones to first take advantage of the business profits that come with the industry’s developing tools.   As the industry of BI continues to progress, businesses will also be able to reap the benefits in their sales and decision-making skills and by cutting analysts from their team — creating a more lean organization and a more profitable business. It all starts with simplification and the industry is already well on its way.

BI & Business Analytics: Are They The Same?

Posted on May 21, 2015 by Doug Hoogervorst - Big Data, Blog

You’ve definitely heard of business intelligence and you’ve likely heard the term business analytics before. In fact, you probably heard both terms used interchangeably, but you aren’t quite sure what the difference is. That’s expected, as some in the BI community aren’t exactly sure where the two terms diverge into separate concepts.

BI experts actually have several different interpretations as to what the differences are between the two, but there are commonalities in their personal definitions that we’ll highlight here. In this post, we’ll break it down so you have a better understanding of the unique qualities of both business intelligence and business analytics.

How Do You Define Business Intelligence?

There are many fancy words that can be thrown around in the industry, so it’s not uncommon to be overwhelmed by what each of them mean. The term business intelligence has actually been on the decline for the last 10 years in Google searches while the term business analytics has risen.

According to CIO, Business Intelligence is defined as the following:

“an umbrella term that refers to a variety of software applications used to analyze an organization’s raw data. It’s a discipline made up of several related activities, including data mining, online analytical processing, querying and reporting.”

In other words, BI is the entirety of everything you know in regards to data collection, displaying and this includes the analysis portion of the BI process.

The concept of BI (and its tools) is required to run a company efficiently by giving the decision makers the data needed to make high quality choices.

The CEO of BigData-Startups, Mark van Rijmenam makes a great point in differentiating the two concepts when he said, “…both will provide you with different, not less, insights. BI is important to improve your decision-making based on past results, while business analytics will help you move forwards and understand what might be going to happen.”

How Do You Define Business Analytics?

As many will agree that BI’s function is to maintain an organization’s efficiency with the data it provides, business analytics serves as an integral function under the BI umbrella. Analytics takes on many capabilities with several intricate tools that offer several different methods of analysis.

For example, business analytics makes use of your current data to project how your company will perform in the months to come. These functions can be conveniently stored in your BI package in the form of dashboards, reports, data mining or even applications.

Analytics is more about revolutionizing and improving upon your company with the data you collect, while BI serves as a maintenance measure to help you continue working successfully in the present.

As the VP of Engineering at Noetix Products, Pat Roche, put it, “business intelligence is needed to run the business, while business analytics is needed to change the business.”

Still, while many experts have offered their different perspectives on what the fundamental difference is between the two, one thing is clear: both of the concepts work together to offer you solutions for your data collection efforts in the present and the future.

As the term BI has been around for decades now, business analytics is right behind it in popularity. The convenience of having analytical tools within your BI infrastructure, takes away the need to hire analysts in your team. Its integration allows your team members to take over the role and plan for the future with confidence, knowing that your analytical tools have served its purpose well.

3 Tactics to Boost Your BI Production

Posted on May 18, 2015 by Doug Hoogervorst - Big Data, Blog, General

No business owner wants to be at the mercy of their business intelligence technology. While many BI applications can serve your business for a reasonable amount of time, this isn’t the case with most solutions. As you may already know, the requirements and updates that these providers offer are constantly changing and make it difficult for your team to keep your technology up to standard.

In order for you to stay ahead of the curve and reduce your dependency on the technological side for gathering, maintaining and displaying your big data, we’ve listed a few pointers to help you stay on track, regardless of your BI solution.

Prioritize Your Outcomes

Some of the original business intelligence solutions didn’t focus on giving its users valuable outputs. Instead, it employed a bottom-up mentality that emphasized the technology and its glamor. This is why we encourage BI users to NOT get caught up in your BI solution’s characteristics, especially if it’s not providing you with valuable data.

Rather, focus on what you purchased the technology for — tangible information. By using a top-down approach to your business, you should be able to make use out of the critical stats that help you make smarter business decisions. With that said, make sure you have a method to capture key performance indicators (KPIs) and other valuable information to keep your business running effectively.

Don’t Forget About Your Data

Never underestimate the power of your data. In fact, data is everything when it comes to business intelligence. While some BI programs continue to ignore the significance of your data, you shouldn’t. A sure way to lose the effectiveness of your technology is to neglect your data by providing unfinished, doubtful or untrustworthy data and inputting it into your system.

With this said, we urge you to focus on your functional reporting capabilities so you can maximize the use of your data and your current BI solution. Like most tools that you use for your business, the outcome of your work heavily depends on the information that you put into it.

And the more complete, detailed data that you place in your BI solution will make it easier for you to truly implement sound business decisions moving forward.

Technology Isn’t Everything

In the past decades, we were all unable to show crucial business information with the click of a button. At least, not easily. While the 21st century has brought several advancements to the BI community and beyond, it has also dragged in many distractions that hinder progress.

Due to the overwhelming amount of gadgets, tools and buttons that are available, sometimes fancy BI solutions can be more distracting than beneficial. Now, with easily-navigable user interfaces, we can perform in-depth functions in less amount of time. We say this, to say that much of your time spent on a BI application should be on analyzing your data and managing your business.

Don’t forget what the “B” in BI stands for — and make sure that it’s at the forefront of your actions.

In Summary…

We understand that in today’s world there are several trends, distractions, tools and specialists that may pull you in several directions. However, when it comes to your BI solution, the goal should be to make use of your data to make decisions that propel your organization forward.

With tools that should give you clear projections for the coming months, your business intelligence solution should be a benefit not a liability. In sum, by implementing these mindsets as a business owner or manager, you’ll be able to keep your focus on what really matters — improving your business.

What is Big Data Discovery?

Posted on May 15, 2015 by Doug Hoogervorst - Big Data, Blog, General

In the business intelligence community, not much has been discussed yet about big data discovery. However, in a couple of years you should be ready to get real familiar with the term. In fact, the term is so new, as you read the first sentence over, you may even begin to think that a typo was made. We assure you it’s not.

Big data, data discovery and data science are all the tools that make up the newest trend in BI — big data discovery.

Limitations Transitioning into Strengths

In recent years, all three of these components have risen in popularity to give business owners, analysts and managers simpler ways to make use out of their data. At the same time, however, these tools also have their fair share of limitations.

Big data grants its users the ability to store a large volume of various data, but it lacks the affordability and ease of implementation. Data discovery is simple and flexible but fails to deliver a comprehensive capability to explore the information. Furthermore, its analysis, while appreciated, is not as in depth as it could be.

As far as data science is concerned, it provides the analysis complexity with a range of tools and intelligent algorithms, but it is too complex for everyday users to master.

What makes big data discovery truly unique is that within these three different areas, their limitations are the other’s strengths — which makes the value of big data discovery well worth it.

According to Gartner, 2017 will mark the year where big data discovery will become its own market category.

Who Benefits?

The combination of these three useful, but near-perfect tools is going to change a lot of businesses who make use of business intelligence solutions. Its simplicity will make it simpler for users to make sense out of the tricky statistics, graphs and analysis functions. What used to be reserved for specialists to maneuver (data science products), will now be available and more intuitive for a much wider audience.

Now, the users of big data discovery will not eliminate the need for those data scientists. Instead, it will simply expand your team’s knowledge on the subject so more employees can aid your data specialists in analyzing your information.

What to Expect Moving Forward

While all of these innovations are aimed to simplify the way your company gathers, displays and analyzes your company statistics, there is still much room for improvement. And this is why the advent of big data discovery is crucial. While there are some who are aware of the concept, it’s prevalence in the real world is still minimal. So for some, the idea is not even on their radar, but for others, 2017 can’t come soon enough.

The future is look bright for big data discovery nonetheless.

Take this piece of optimism from Gartner as an example:

Big data discovery may require investigation by BI and analytics leaders to seek a portfolio of technologies and tools to be deployed; since no single vendor offers all the components required, from data access to advanced analytics.

Big data discovery will help expand the use of big data analytics because exploration of big data sources will occur more often, much faster and at a lower cost per analysis, delivered by a broader range of users with more rudimentary technical skills.

The Pros & Cons of Data Warehouses

Posted on May 7, 2015 by Doug Hoogervorst - Big Data, Blog, General, Reporting

Your BI solution’s data warehouse (DW) serves as one of the initial checkpoints for your important business data. Your DW is a repository where your data is stored electronically before the data is able to be reported and analyzed. As a whole, this portion of you BI solution is also in charge of loading, managing and extracting this data.

While this tool is certainly useful for many businesses, not every type of DW is relevant to your business makeup or industry, even. This is why, in this post, we’re going to break down the essential pros and cons of data warehousing, to ensure you make the right choice when choosing yours.

PROS of Data Warehousing

– Speedy Data Retrieving

How many times have you had a piece of information that you wanted to retrieve, but forgot where it was placed? Once you input your information into your DW, you will never lose track of this data again. By conducting a quick search, you’ll be able to find the statistic and further analyze it — without having to waste time in your search.

– Error Identification & Correction

Many of us have the natural tendency to skip over dotting the I’s and crossing the T’s when inputting raw information, but data warehouses help eliminate user oversight. Before loading data, your data warehouse makes it a point to show you inconsistencies and correct them. This is extremely helpful for those who may be careless or hasty when it comes to gathering data.

– Easy Integration

Your DW also adds value to operational business applications like CRM systems when the warehouse is successfully integrated. The complexity of its makeup allows a data warehouse to translate the information in a more simple, digestible format to the point where your team members can easily understand what’s been placed in front of them.

CONS of Data Warehousing

– Time Consuming Preparation

While a major part of a data warehouse’s responsibility is to simplify your business data, most of the work that will have to be done on your part is inputting the raw data. Now, while the job the DW does for you is helpful and extremely convenient, this is the most work you’ll have to manually perform, as the DW performs many other functions for you.

– Difficulty in Compatibility

Depending on the system you currently have in place, the use of data warehouse technology could likely require a helping hand from an independent BI team. With the intricacies of operating systems, software and programs, it can be difficult for a business owner to figure out how to properly make use of their data warehouse. Especially since the costs of these tools are investments in your business, you’ll want to ensure that your system is working exactly the way you intend it to.

– Maintenance Costs

One of the pros and cons of your DW is its ability to consistently update. This is great for the business owner who wants the best and latest features, however these upgrades don’t usually come cheap.

Including regular maintenance for your system, you can expect to shell out more than your initial investment should you want to have the latest technology at your fingertips.

– Limited Use Due to Confidential Information

If you have sensitive data that should only be viewable from a certain staff members, your DW’s use will be limited. In order to maintain the security of your current system, less usage could eventually decrease the overall value of your data warehouse.

No matter your needs or concerns, our specialists at Business Impact look forward to helping you make the right decision when it comes to selecting the right BI solution for your company. Contact us today to learn more about how we can help your organization get the most out of its business intelligence solution.