Supercharge your NetSuite reports with ZoneReporting

Struggling with complex financial reporting that your current NetSuite setup can’t handle? You're not alone, and we’re here to help.

Our NetSuite reporting wizards Ken Loewen (Solutions Architect + CPA, CGMA, CMA, PMP) and Scott Pickering (Engagement Manager + former Big Four CPA and CFO) share how companies just like yours tackle tricky reporting challenges using ZoneReporting and Power BI. You'll learn:

• Why typical NetSuite setups fall short when reporting gets tough
• Real-life stories about companies overcoming complex financial reporting hurdles, like complex inventory demand planning
• A live demo showing how ZoneReporting aligns your data to your business—no costly NetSuite reconfiguration needed

Whether you're dealing with reorganizations, acquisitions, or evolving business needs, you'll walk away with clear ideas and practical steps to get more from your NetSuite data.

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Transcript

Michelle Voznyuk: So I know we have a packed agenda today, so we'll go ahead and get started. Thank you guys for joining today on our session about supercharging your NetSuite reports with ZoneReporting. Really excited about the content we have ahead. Before we get into that, just wanted to cover a few housekeeping items.

First with the Q&A, we have that enabled, so if you have questions throughout the webinar, feel free to throw them in. Scott and Ken, our hosts will try to answer those as they can. We also have some time at the end of the webinar that is dedicated to questions as well. So if we don't cover them during each section, we will have time at the end.

The chat is disabled for this webinar, but again, feel free to use the Q&A. And just to let you know, this will be recorded. So we will send out, the recording for the webinar at the end, usually within the next day or so.

And then as far as our agenda goes, we're going to cover who Zone is, if you're new to us; why typical NetSuite setups fall short stories about companies overcoming complex P&L challenges, and then get into a live demo of ZoneReporting. And then again at the end, do that Q&A session.

So just a little bit about us. If you're new to Zone, we provide NetSuite native solutions for accounting, finance, and payroll that take you from impossible to unstoppable. We are currently serving over 4,000 customers globally. We have a staff of about 250 people. And then we have 10+ years of experience with NetSuite.

And so these are some of the solutions that we offer today. We're going to be focusing specifically on ZoneReporting, and then with that, I will turn it over to your hosts, Scott and Ken, who will introduce themselves and go ahead and kick us off.  

Scott Pickering: Thank you, Michelle. I'm Scott Pickering and my role at Zone is an engagement manager, and what I do is develop and assist clients with their reporting solutions.

My background is in finance accounting and it certainly started out as a big four CPA and most of my career is in private industry in FP&A and later as a CFO took a software company public. The last 10 years, I've really been dedicated to business intelligence. That means developing SQL data warehouse, data models and reporting solutions in Power BI.

And that's what we have here the last five years at Zone building out these reporting solutions for you that we're going to show you today, Ken.  

Ken Loewen: Hi everybody. My name's Ken Loewen. I am a solutions architect on the ZoneReporting team. And like Scott, I started my career primarily in finance and accounting.

I transitioned pretty quickly away from the routine debits and credits over to ERP implementations and system transitions, spending a number of years in Big Four consulting and have been working with Power BI for about 10 years. So, really excited to be talking with you today.  

There are two major roles with regard to working with Power BI, which is the delivery platform that we use for the ZoneReporting solution.

You can purely be a consumer of reports somebody else, either somebody in your organization, or somebody that you brought in as a consultant or somebody on the ZoneReporting team can create reports for you and any and all of the people on in your organization can merely consume those reports. That's very valid. That would tend to be the majority of the people involved in this.

Then alternatively, you could be a developer. So we are perfectly happy to equip you to modify pre prebuilt reports that we provide to you as part of your ZoneReporting implementation, and also to help you to upskill yourself and members of your team to modify and develop reports that address your very specific reporting challenges.  

So perfectly happy to work with you on either or both of those anywhere in the spectrum from the: you say, this is great, I'm going to go off and build reports. I don't need any help, to you come to us once in a while for help dragging something across the finish line, to the, no, I really want some help building a report. Glad to help with that.  

Let's move on a little bit and talk a little bit about our problem statement today that we're talking about, and the issue is that sometimes NetSuite reporting struggles to keep up. It struggles to keep up when things get really complex for you.

Some of the specific technical barriers that you may have are that NetSuite only allows you to join two tables at one time, whereas in the ZoneReporting solution, because we're moving your data into a fully featured data warehouse in Microsoft Azure SQL, you can have unlimited joins between data, and that just provides you a ton of additional flexibility.

A lot of times organizations are going to solve their reporting challenges by exporting the data to Excel and then requiring somebody, and often it's the executive who's trying to do the reporting, that somebody has to further manipulate the data.  

When instead, if you use ZoneReporting, one of the things you can do is you can configure a report that takes you all the way down to the specific insights that you want the report consumer to use to apply for his or her job.

So due to those challenges, a lot of organizations struggle to get timely, accurate information, and that's in a normal routine situation. What happens when your organization experiences mergers and acquisitions activity, or reorganizations? Those heroic reporting efforts that people have been expanding or expounding on just get compounded- increasing the delay, increasing the opportunity for errors to creep into your spreadsheets. So that you're increasingly dynamic, very challenging business environment becomes less responsive.  

We often work with organizations going through a maturation phase with their NetSuite, where their business processes become more complex. They're getting more and more features and more and more value out of their NetSuite implementation. But they find that while they can model the effect on their historic data offline, the effort to restate all those changes in NetSuite is unacceptably high. We can work with them and remodel data into the data warehouse outside of NetSuite, helping you to avoid expensive NetSuite reconfigurations when your business changes.

So the solution: modernize your reporting without overhauling NetSuite. You can continue to leverage NetSuite's capabilities to support all of your transactional processes and to capture the data that's flowing from their processes while supplementing the NetSuite data as required. ZoneReporting is set up to extract as much of your NetSuite data as is necessary in order to address your requirements and brings the power of a data warehouse and Microsoft Power BI to bear to provide your reporting and analytic analytical power.  

We also provide prebuilt reports to demonstrate the use of your organization's NetSuite data and demonstrate helpful report building techniques to you while serving as a jumping off point for creating purpose-built custom reports that address your exact needs.

A lot of companies have complex reporting challenges. For example, when the chart of accounts doesn't match the way your leadership team needs to see the data, or you refigure the entire way that your sales or marketing team is aligned against your product portfolio or something like that, and you don't want to go reconfigure your NetSuite, but you can reconfigure your reporting without having to do that.

So Scott's going to give us a live demonstration of how we go from a prebuilt report, just like you get with the ZoneReporting implementation to supplementing your NetSuite data with some additional data and getting to a more fully featured report that supports business processes. And then quickly developing custom reports that take you all the way down to the specific insights.

So at this point we're going to talk about our demand planning use case, and I'll hand it off to Scott to talk a little bit about that.  

Scott Pickering: Thank you Ken. Go ahead to the next slide please. This is a- go back up. The graphic is showing the six different reporting packages that we have developed that work with NetSuite and most of our clients take financial and SaaS or financial and supply chain. And today we're going to focus on the supply chain part of the solution for our use case. Next slide.  

And what we're going to look at specifically is demand planning. So why do we want to have demand planning to optimize your inventory levels, right? And avoid lost sales. And we want to look at any slow moving inventory to balance that out and that means improving turnover and we're going to also reduce carrying costs. And avoid production delays when we have parts that are critical for assembly and that leads to higher profit and ROI. So that's why we're going to focus on demand planning now. And next, please, Ken.  

So we're going to talk about supplementing your NetSuite data. So in this demonstration scenario. Let's go to the supply forecast. We have to do supply and demand, but on supply, we use open purchase orders in NetSuite, and that provides a pretty good forecast for future sub inventory levels because those inbound deliveries are usually scheduled several months into the future, and they're sufficient quantities.

But on the demand side, not so good. Often your open sales orders have been mostly fulfilled, and you don't usually get sales orders to deliver well out into the future. So we don't have enough quantity in NetSuite to do a demand forecast, so we supplement it with an updated sales forecast.  

And so the prebuilt inventory report that we're going to show has a place for this supplemental demand plan. Right now it doesn't have any data in it, and we're going to put the data in there and show how it works when we put it together.  

That same case, that where we add non NetSuite data, we can do that for budgets, forecasts, historical data. Today we're going to use it for demand plan.  

Now this is a data flow diagram and data flow diagrams always go from left to right.

The way this works is we start over on the left here with saved searches from NetSuite. We bring those into the Azure blob. They are processed and transformed in our data warehouse. The data model in Power BI consumes that data, prepares it for reports on the right. That's the big flow of how the solution works.

The next slide, please. That today's example, we're going to go in this top left. We're going to start with the sales forecast, convert it to a demand plan in CSV, upload it to the blob, and we'll go. We don't have to go to the data warehouse. This one can go straight to Power BI, where we develop reports. That's today's flow.  

We have the opening page of the ZoneReporting supply chain model, and there's a few things I want to show you about how Power BI works. Over on the right are the actual tables that come in from NetSuite. So you'll recognize some of these that we might have. Chart of accounts and class currencies, customers, employees, locations, right? And we also have added a number of inventory measures, KPIs, that are all part of this, that are part of the total solution for supply chain reporting.  

And the way this works is, I'm going to go over here to the model view on the left and show you how demand plan is connected. So we have a demand plan. It actually has six columns, and you'll see that it's linked in a data relationship to the transaction date, the demand date, and the transaction date. We have connected to the items table, through the item internal ID, and over to the locations. So that's how the structure works. Now, the whole data model is much bigger than that. There's many more tables that all work together, but today we're just going to focus on those related to the demand plan.

And now I'm going to show you what ends up looking like the demand plan. By look at it, you'll see there's these six columns, but no data. So that's what we have to build the data to supply these roads, and that's where we're going to go first.  

So if I don't have any data, where do I get it? If I'm helping the operations team with managing inventory levels, I'm going to coordinate with my sales team, and I'm probably going to get an Excel forecast that looks something like this.

So if the sales team has sent us a sales forecast, it's going to have some locations over here. It's going to have some items and it's got, these are weeks, so these have dates out there. They might be months or weeks. This example, we're using weeks and we've got all these quantities of what's they project will be sold.

So we're going to start with this as our source in Excel. And usually there's some totals and things and as an example of, okay, let's put that in our data model. Well, we don't have the right columns. We saw we need six columns, and then this is giving us too many. So what we need to do is unpivot this data.  

And straight in Excel there's no Unpivot command, so we have to use a feature within Excel called Power Query to do the unpivot. And you don't start with this report. We're actually going to make a new blank page in Excel this way. And we start with this page. What we do first is we go to this data tab and inside data, we go to get data from File from Excel workbook, and it's going to load my sales plan.

I go to the sales forecast table, it's going to connect to that table and load it into Power Query, which is a different menu, and it's going to show me that here's my workbook and here's my worksheet. There's only one worksheet in this file and it's already previewing what I'm going to have, I'm going to go down to this transform data button, right?

And it's going to open up my Power Query window, and I get a look at what the table had for me to work with. And what I find first is that the column headers aren't in the column header position. So good news is there's a little button here called first row headers you ever hover. It'll tell you promote the first row of this table to headers, and that's the first step. Now I have all my headers.  

Now the other thing we noted is we have to get down to the six columns, the right six columns, and we do not require location name, we just need IDs. So humans need the names, computers need the id. So we'll take those two and we will go over here and just remove those two.  

Now we have these two columns, which we do need to keep, right, and there's a transform button over. Here's your unpivot. So what I'm going to do is I'm going to unpivot all the other columns, the ones that have dates and have amounts. I want to unpivot those and instantly I'm down to four columns. So that's really good news. It's going to name these. This way I need to rename them. So I just double click on it. And this is going to be demand date. Okay? This one over here will be quantity.  

So now I have four columns, but they're not quite right yet because this one, if I filter on it by hitting that little button, I still have totals in there. I don't want totals. So I'm going to filter those out. And in the item, internal IDs, I have some totals too that sales gave me, so I want to remove those.  

And then finally, in the demand date, there's some totals. So I remove those. So now I have four pretty clean columns, but I need six. So how do I get the other two? I go over to this add column and I can make a custom column, and the next one I take is called demand plan internal id. And I can make this any number I want. I'll just make it 1002, for example, as a placeholder that I could have multiple demand plans over the course of things. But that's the number for this one.  

I'll make one more custom column, and this one needs to be last modified date and I could put any date in here, but I, my example here is going to be 5-11-2024.

So we're going to have a time machine and we're going to go back to 5-11-2024 for the purpose of this forecast, because that's when my demo data works. Now I have my six columns, and you'll notice that I haven't done a thing to my data types because I'm going to turn this into a CSV file. And CSVs don't care about data types, they're just text anyway.  

So with those six in place, I now go to home, close and load. It's going to take that Power Query window and it's going to bring it back into Excel. That looks like this. And you've recognized this. It looks, it's a table, right? It's got all my data. Now I've got those six columns. All of my dates are in this column, right? And all of my quantities are in this column. That's what the computer needs to consume this data and put it in the data model.  

Now I want to turn this into a CSV file. So the way I do that is I can't have two sheets in a CSV, so I just delete this one. And now with this here, all I have to do is do a save as. And I'm going to go up to my desktop. I'm going to save this as of a, I'm just going to call it demand plan because that's what it's called in the blob, right? And what type of file do I want? I want a CSV file. So now it's going to take that data and it's going to save it as a CSV now I'm going to replace it. Now this data will be in my, uh, right now it's on my local drive, but I need to put it in the Azure blob.

So if I go to the blob, it looks like this and they blobs have names, accounts, and containers. And we're going to look at this little container here for the webinar, okay? And you'll see there's already a demand plan because that's the one with no data in it. I need to upload and replace it. So I hit this upload button, upload files, and I have to pick the file, which is going to come from where I put it on my desktop, right?

And there's my demand plan csv. It's going to check and I'm going to try to upload it and it's going to come back and say, Hey, wait a minute. You already got one named that. I go, exactly. I want to replace it with the good data. So I'm going to apply. And now we got a green check. That's what we wanted. Green check. We know we're good. All right. So what we're going to do now is we're going to go to our supply chain report. We'll notice that in the definitions we already have DAX that calculates the supply quantity and how does it calculate supply open PO quantity by expected receipt date, which is a pretty good forecast.

You can see we have 30,000 units coming in in future POs and if there's any open work orders, we pick those up and in this case, there's no transfers. The demand quantities already predefined as open sales orders. As you can see, there aren't many. There's no transfers, but this last piece is what we're going to get from the data we just uploaded. The demand plan quantity will now be able to populate.  

So when I go to my predicted projected inventory report right now, what I have is on the left here is our count. This came from the location inventory that table we get from saved searches. Then we have this graph shows the inbound purchase orders, the green, which is supply. And this calculates the quantity of each week. It's keep going up. It's going from 200 to 230,000 because we're just bringing in more stuff and we haven't been selling it yet. We don't have a demand in there.  

So what we want to do is now refresh. So if I go to the demand plan over here on the right, and I refresh this. Now that data I just uploaded to the blob is going to come in. Those 344 rows are loaded. It's going to populate this report. And now the demand quantity is now appearing in red.  

So these are shown as subtractions from inventory because they're going to be coming out. And you'll see that the quantity goes down, not 230, but down to 130 because we have a 100,000 units of demand that's in here, and we know exactly when they're coming in by week.

All right, so this helps us identify what we have. We have a little slicer here that will take us by class, and it tells us that some of these are going negative. And some are going positive, so we're going to have to analyze further. And the way we do that is we're going to create a new report that we can take action with .

Ken Loewen: And before we do that, Scott, we've got a great question from a participant in the webinar asking which of the features that have been demonstrated are custom features versus outta the box. And I thought that was great. Everything Scott demonstrated in Excel is a standard feature of Excel that you all have in Excel today.

Scott mentioned Power Query. It's been in Excel for well over a a dozen years. The report that Scott is showing you right now, the projected future ending inventory report is a standard report that you get in deployment of ZoneReporting with the supply chain prebuilt reports. Scott is working with demo data.

So this report standard has populated with data that's in the demo data. So the idea that he's using class, which you'll see on the far left of that highlighted projected inventory box. That would populate with your values for class or your item numbers, as Scott has demonstrated that. So at this point now, Scott's going to proceed into customizing the out of the box report.

Scott Pickering: So what I've done is I've just cloned that out last page, and I'm going to change this into what we're going to call stockout risk. So I'm just changing the title so you can see that that's what we're going to do. But the title doesn't change anything. We need to add values, right? We need to change the filters in this.

And how would I define stockout risk? I'm going to filter this where anywhere my ending inventory is less than zero. And when I apply this filter, I've now changed this matrix into a report that tells me exactly which items are projected to go negative. So these are the items I know immediately. I want to cut a new purchase order for to make sure we have plenty of inventory.

And then if I just duplicate this, I can make another little report. And I'm going to call that my slow moving risk. And that one is I'll, we'll just call this slow moving. And how would we define slow moving? We want inventory, let's just say anything greater than 10 is a place to start. And then we also going to look where demand is zero. So if demand is zero and we still have a small amount of inventory, that's going to tell me that's my slow moving report. So when I sort this, I now know that these are the items that I have long on, right. These are the items I'm short on. So we're going to go through these one by one as a card. As I look at that notice, it's projecting to be negative. So I know these are the exact items I want to go create a new purchase order, and I don't have much of a risk of slow moving here on Chip, it's the opposite story. I have a lot of these that aren't selling at all. And guess what? I've got purchase orders coming in. So what do I want to do? I want to cancel those purchase orders most likely, right?

I got a few that are short, but mostly I want to cancel purchase orders in the chip category. And there's the specific ones I want to do. Now, if I go to clamps, you'll see a big drop here. We're cutting up our inventory in half. Some of those are short. These are long. I'm going to have a discussion with my sales guys and say, if you're promoting these, can you promote that one too?

Or can this one substitute for that one? Don't know, but we're going to ask, right? So we have a little bit of work on balancing inventory. Uh, dram. Pretty flat. We have one to order, but most of this is all right. If I go to fans, I also have a negative, so I have to order more of these to get them in stock. And I've got a lot of these that are long, so I may want to promote change, price or take actions to be able to handle that.  

And then finally, on my systems, I have a big decrease from 12 down to 2000. And we were still short more purchase orders to get stuff in to meet the demand. And now we've got some of these we probably want to discount and move on.

So that is the method of doing all this stuff.

So let's recap what we did. We started with a prebuilt inventory projection report, but it didn't have enough demand data, right? Then we took a sales forecast Excel sheet from sales, and we transformed it into a demand plan using Power Query Unpivot. Then we uploaded that into the Azure blob, and then we refreshed the Power BI data model with that updated data and it populated in Power BI.

So the next page is what we did to analyze and take action. We looked quickly at the graphs. The visualizations told us we had some things to adjust. We knew we were long and short on items by class, by week and next what we do is, we create action reports. So the last page, we created two quick reports.

One for stockout risk, one for slow moving. This is an example. You don't have to stop there. You can make many more reports. But we have a platform that allows you to do that. So we have this detailed listing that now you can take straight to your buyers and make those changes to purchase orders, right?

You create new ones, cancel existing, and then we're going to talk to sales and marketing about those slow moving items. So we're going to do some other actions in sales and marketing, pricing, promotion, and so forth. So it leads to corrective action and improving the company. Right? And what else we got?  

That's just an example of some of the reports we have in our base package In the prebuilt, we only looked at one, but there's many more that you can build or expand on and use for inventory management.

Some other examples of things. You could build additional KPIs that aren't in our reports that you can add stock out rate. There's more. Just click through those if you would, ken. Fill rate back, order rate, lost sales. Many more things you can build from here depending on the unique things on how you manage your inventory and how you do your business. So this is supporting operations and sales, not just finance and account.

One more. You can even make more reports, right? You can make a stock out and back order report, for example. You want to look at how these affects back orders, lead times your replenishment process. We didn't build a whole EOQ model here, but you could, right?  

Maybe you have another third party tool to work with. You could integrate the data from that into our Power BI solution and some aging.  

Ken Loewen: Scott demonstrated out of the box capabilities. Power BI Desktop that he opened when he opened that prebuilt report is a free tool that you get from Microsoft that allows you to modify existing prebuilt reports and create your own reports. An infinite number of new reports in Power BI desktop, using the ZoneReporting data model.

We do have a question in the chat. Let me pull that up. If you have an assembly made of 10 parts and the demand plan is made based on sales orders for the assembly item, will it display stockout projection of the parts that make up the assembly or just the assembly?

Scott Pickering: The answer in this demo is it's just going to take the finished good. All right. But you're going to have a bill of materials explosion inside your NetSuite so we can supplement it to make sure we generate all the dependent parts for that assembly.  

Ken Loewen: So it's fairly easy in the data model to exclude items that are in assembly from the inventory stockout report and say, based on the math that you're doing in the backend, tell me which raw components or sub assemblies are going to be impacted by our demand forecast.

That's great. Got another question from Richard. How do you deal with refresh from NetSuite example? Do you have refresh button or is this set to a time? I can take that one. So. At your base implementation of ZoneReporting, we set saved searches up in NetSuite using NetSuite's standard saved search capability. And those export the data from NetSuite into the Azure blob storage, which is where Scott showed uploading the demand forecast. Those are scheduled to refresh approximately four times a day. Um, there are increased refreshes available if that's necessary. And, and so the times for those four times a day would be set based on your business processes.

So if, for example, you push a bunch of orders out just before lunchtime and you want it to refresh over the noon hour and have your team come back at one o'clock and check on the data and, and take action across the afternoon based on what happened at the end of the morning, that's very realistic. A lot of times overnight refreshes work great, and you start the day with data as of close of business.

Any other questions? How do you deal with calculated fields in NetSuite? Example P&L year to date? Do you duplicate these in your data cube or duplicate the calculations? Great question. We've got a feature in the ZoneReporting data model that we call Time Intelligence calculation groups. And this is a standard feature of Power BI. And what we do is we define what are the time intelligence functions that we want to apply. So for example, we want to know about month to date, prior month, prior month to date. So there's a distinction there. Year to date, quarter to date, we want to know month to date over prior month to date, quarter to date, over prior quarter to date.

The base implementation has got about 30 of those different time intelligence functions, and what you then do is you take a measure that provides a calculation. So that might be inventory supply. You overlay it, which with whichever one of these time intelligence calculation items you want to know about, and you just check some boxes and say, I want to know that, uh, supply quantity for the month to date. I want to compare the supply quantity to the prior month to date.  

And it, it literally, it, it takes less time than it just took me to describe that, to apply those functions. And you can supplement the data model very easily with additional time intelligence functions. So if you want something that's not in there, that is important to your business, although our model by default handles, both fiscal year calendars, calendar year calendars also, if your organization is on a 4-5-4, um, or a 4-4-5 or a 5-4-4, um, we handle all of those out of the box.

Um, okay, great. Uh, I was going to get to the, I touched on this a little bit. Uh, so this question is how do you deal with things like chart of accounts, differences from NetSuite? I want it to look differently. Do they have a mapping in the data model or is this something else? Your problem statement is of an infinite size.

There are so many different ways to describe this, but it's a very reasonable, very frequently occurred, sit or encountered situation in my experience, specifically, um, where the client wants some sort of a report structurally different from the way that NetSuite is set up and there are a variety of approaches to do that based on how the, um, the scenario presents itself.

So often we'll have some sort of a mapping table that we will upload. Um, sometimes it's upload once, sometimes it's upload once and then refresh it periodically. But we do encounter that quite a lot. I had a client that used, department numbers to organize their P&L, so they had some departments that made revenue, uh, uh, departments, some that were COGS departments, some that were OPEX departments. And our, our base P&L wasn't structured exactly that way, but it was a, a mapping we were capable of doing.  

I've got a client right now where they have a lot of historic data that doesn't contain as much of the detailed analysis information as their current data. So they have a, a series of contracts running and the historic contracts don't have as much data. So we're supplementing that with a table that is, uh, analyzed and manually uploaded with the supplemental data. So it's really handy to not have to go back and reenter your old transactions in NetSuite or try to. Um, but usually it would be a, you know, reentering old data. Um.  

Then one of the things we did mention on the slides is we could also handle all manner of historical data, like the data from prior to you being on NetSuite and say, Hey, we want to go live on NetSuite now, but we'd really like to compare our first quarter on NetSuite to the first quarter of the prior year before we were on NetSuite. Yes, that's, that's, uh, easily handled.  

Scott demonstrated supplementing the demand plan where a blank demand plan is already in the data model. And that is a very reasonable, um, situation where you literally can do exactly as Scott did. He wasn't demonstrating anything that required, you know, administrator access.  

There are many ways to supplement your data above and beyond the prebuilt demand date, uh, demand plan table, or the prebuilt budgets table, both of which are blank in the base implementation, um, to, to achieve other circumstances. And so we're more than happy to talk with you during the, the presale cycle or, uh, during the implementation phase about what these further customizations might be.

Uh, for this to work from NetSuite, do you need analytics or ODBC links, et cetera? No, you don't. Uh, this the ZoneReporting solution doesn't require anything from NetSuite, aside from running those pre-configured, saved searches that our implementations team will set up.  

Once those saved searches are in, they extract the data from NetSuite. It moves the data using a suite app we call tactical Connect into the Azure Blob Storage, which is a very inexpensive online storage platform. And the data warehouse and Power BI ingest the data from the Azure Blob Storage. So at that point, all of your report building, all of your analytics occurs in Power BI.

Um, Power BI brings you both an online data consumption platform called the Power BI Service. That, that you get to through a web browser. Uh, so your people who are primarily report consumers will be opening those reports either in their web browser or in an app on a mobile device. Those who are creating and modifying reports, uh, will primarily be using Power BI desktop on a PC. If you use Mac um, I've been told that it works really well in parallels. Uh, I don't have firsthand experience with that. There is a web editing experience, but I don't find that it's quite yet, uh, as fully featured as using Power BI. Kind of similar in my mind to do I use the Web Excel application or do I use the downloaded and installed Excel uh, application.

Michelle Voznyuk: Thanks, Ken and Scott, I know we're at time. Thank you all for joining. I hope you found this session valuable. Again, we will send out the recording after the webinar. And with that, I will let you get back to your day and hope to see you guys on the next one.  

Ken Loewen: Thanks everybody.  

Scott Pickering: Thank you.