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Making the Best Use of V6 SQL OLAP Functions

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Getting the most benefit out DB2 for i requires keeping the concept of "set at time" in mind and making use of all the latest features and functions.

By Mike Cain

In Dan Cruikshank's August 2008 article "Working with Data Sets," Dan illuminated the power of SQL "set at a time" processing, and he used some of the new DB2 for i 6.1 OLAP functions to do it. In this article, I'll expand on this concept and demonstrate some additional uses for OLAP functions, as well as reiterate the reasons that SQL can be so powerful for the data-centric programmer. We'll also take a look at some of the performance considerations for more-complex SQL requests.

 

First, a review of the SQL OLAP functions available as described in the DB2 for i SQL Reference publication:

•·                RANK or DENSE_RANK specifies that the ordinal rank of a row within the window is computed. Rows that are not distinct with respect to the ordering within their window are assigned the same rank. The results of ranking may be defined with or without gaps in the numbers resulting from duplicate values.

RANK specifies that the rank of a row is defined as 1 plus the number of rows that strictly precede the row. Thus, if two or more rows are not distinct with respect to the ordering, there will be one or more gaps in the sequential rank numbering.

DENSE_RANK specifies that the rank of a row is defined as 1 plus the number of preceding rows that are distinct with respect to the ordering. Therefore, there will be no gaps in the sequential rank numbering.

 

•·                ROW_NUMBER specifies that a sequential row number is computed for the row within the window defined by the ordering, starting with 1 for the first row. If the ORDER BY clause is not specified in the window, the row numbers are assigned to the rows in arbitrary order, as returned by the subselect (not according to any ORDER BY clause in the SELECT statement).

 

•·                GROUPING SETS allows multiple grouping clauses to be specified in a single statement. This can be thought of as the union of two or more groups of rows into a single result set.

 

•·                ROLLUP is an extension to the GROUP BY clause that produces a result set containing subtotal rows in addition to the ″regular″ grouped rows. Subtotal rows are ″super aggregate″ rows that contain further aggregates whose values are derived by applying the same column functions that were used to obtain the grouped rows.

 

•·                CUBE is an extension to the GROUP BY clause that produces a result set that contains all the rows of a ROLLUP aggregation and, in addition, contains ″cross-tabulation″ rows. Cross-tabulation rows are additional ″super aggregate″ rows that are not part of an aggregation with subtotals.

 

To set up our simple example, let's assume we have three tables that describe students, classes enrolled in, and activities signed up for (Figure 1). The classes and activities are related to students by the studentid column.

 

create table students (studentid int, studentname char(20));

create table classes (studentid int, class char(20), fee decimal(7,2));

create table activities (studentid int, activity char(20), fee decimal(7,2));

102208CainFigure1.GIF

Figure 1: Our example shows students and their classes and activities.

 

Our job is to produce a report that shows all students along with their respective classes and activities, the fees associated with each class and activity, the total class and activity fees for each student, and a final total of all fees represented in the set (Figure 2).

 

102208CainFigure2.GIF
Figure 2: All students' class and activity costs are totaled. (Click images to enlarge.)

 

Looking at the report, we see that the various activities and classes for each student are not related, yet we need to fully populate each line of the report with information. At first blush, this is not a trivial task, especially if we want to minimize the number of passes through the data. Enter SQL and OLAP functions.

 

To understand how to accomplish this with SQL, we must recognize the work that needs to be done based on the given data model.

 

For each student, we must list the classes and the fees associated with these classes, calculate the total fees, and then order by student. The following SQL statement represents this request:

 

select            s.studentname,

            c.class,

            sum(fee) as total_class_fee

from        students s,

            classes c

where       s.studentid = c.studentid

group by    s.studentname,

            c.class

order by    s.studentname;

For each student, we must also list the activities and the fees associated with these activities, calculate the total fees, and then order by student. The following SQL statement represents this request:

 

select            s.studentname,

            a.activity,

            sum(fee) as total_activity_fee

from        students s,

            activities a

where       s.studentid = a.studentid

group by    s.studentname,

            a.activity

order by    s.studentname;

 

If we were to union the two results together, we would most certainly provide all the results in one set, but the report will contains holes or gaps. In other words, the rows representing classes and activities for each student will be listed vertically, not horizontally. We need to somehow get the class and activity information condensed into as few rows as possible. We need to "drill across" each set of results to find all classes and activities for each student (Figure 3). In effect, we are pivoting either the class information or the activity information up so that it appears alongside the student information horizontally.

 

102208CainFigure3.GIF

Figure 3: Drill across the result sets.

 

The big question is, how do we accomplish this with SQL against our simple relational data model? Part of the answer entails using a left outer join. Specifically, using the distinct set of students on the left and joining to their respective class and activity information on the right. By using a left outer join, the database engine will return the student information even if there is no corresponding class or activity for that student.

 

But how do we know if a student is associated with any activities or classes? And how do we determine the number of lines each student will need to represent their condensed list of classes and activities? Enter ROW_NUMBER OVER. With the ROW_NUMBER function, we can have DB2 assign a number to each intermediate result and use it later. Furthermore, if we use the OVER clause, PARTITION BY clause, and ORDER BY clause, we are able to assign distinct numbers to each result, by student, and have these results ordered by class or activity (Figure 4). We will include grouping criteria in case the student is signed up for the same class or activity more than once. The enhanced SQL statements would like this:

 

select      ROW_NUMBER() OVER (PARTITION BY s.studentname

ORDER BY c.class) AS row_num,

            s.studentname,

            c.class,

            sum(fee) as total_class_fee

from        students s,

            classes c

where       s.studentid = c.studentid

group by    s.studentname,

            c.class

order by    s.studentname,

            row_num;

select      ROW_NUMBER() OVER (PARTITION BY s.studentname

ORDER BY a.activity) AS row_num,

            s.studentname,

            a.activity,

            sum(fee) as total_activity_fee

from        students s,

            activities a

where       s.studentid = a.studentid

group by    s.studentname,

            a.activity

order by    s.studentname,

            row_num;

102208CainFigure4.GIF

Figure 4: The results are ordered and numbered.

Notice that each student now has his respective classes and/or activities ordered and numbered. Keep in mind that the row number is actually part of the result set.

 

To obtain the list of students who have classes, activities, or both, we can run the following statement against the results from classes and activities. Recall that UNION removes duplicates for the result set. Also notice that we want to order the results by studentname and the row number assigned by DB2 (Figure 5).

 

select      studentname,

            row_num

from        intermediate results from the previous query - Figure 4

union

select      studentname,

            row_num

from        intermediate results from the previous query - Figure 4

order by    studentname,

            row_num;

 


102208CainFigure5.GIF

Figure 5: These are the results of merging the lists together via UNION.

 

The result set tells us not only the students who have either classes or activities, but also how many lines it will take to show the information. As the next step in the process, this list of distinct studentnames and row numbers will be used to drill across the classes and activities via a left outer join.

 

select              t3.studentname,

t3.row_num,

t1.activity,

sum(t1.total_activity_fee),

t2.class,

sum(t2.total_class_fee)

from                intermediate results from the previous query - Figure 5

left outer join intermediate results from the previous query - Figure 4

on (t3.studentname = t1.studentname

and t3.row_num = t1.row_num)

left outer join intermediate results from the previous query - Figure 4

on (t3.studentname = t2.studentname

and t3.row_num = t2.row_num)

order by          t3.studentname,

                        t3.row_num

t1.activity,

t2.class;

The results of the left outer joins might look like this (Figure 6):

 

102208CainFigure6.GIF

Figure 6: Here are the results of a left outer join.

 

Now that we have each student's information condensed into the fewest number of lines required, we can turn our attention to providing class and activity fee totals by student and ordering the results (Figure 7). For this, we will use the new OLAP feature grouping sets. In our report, we have three sets of grouping criteria to sum up: fees for each line of the report, fees for each student, and grand totals for the report--namely (studentname, row_num, activity, class), (studentname), and (). The SQL used to drill across and aggregate the data looks like this:

 

select            t3.studentname,

t1.activity,

sum(t1.total_activity_fee),

t2.class,

sum(t2.total_class_fee)

from        intermediate results from the previous query - Figure 5

left outer join intermediate results from the previous query - Figure 4

on (t3.studentname = t1.studentname

and t3.row_num = t1.row_num)

left outer join intermediate results from the previous query - Figure 4

on (t3.studentname = t2.studentname

and t3.row_num = t2.row_num)

group by grouping sets ((t3.studentname, t1.activity, t2.class),

(t3.studentname),

())

order by    t3.studentname,

t1.activity,

t2.class;

102208CainFigure7.GIF 

Figure 7: Now, we have class and activity fee totals by student.

 

Now that we have the various pieces and parts to arrive at our final data set, let's put it all together. While we certainly could use multiple SQL statements and actual intermediate tables to do this, let's use the power of DB2 to do all of this work with one SQL statement. To do this, we will take advantage of common table expressions. Recall that a common table expression permits us to define a result table (with a table identifier) that can be specified as a table name in any FROM clause of the full select that follows. This will allow us to define and build all of our various intermediate results and then perform the left outer join and grouping--in one SQL request. Doing this also has the advantage of allowing the DB2 for i optimizer and database engine to perform all the work in microcode, eliminating the need to materialize true temporary tables. It is also possible that there will be additional benefit from overlapping I/O and data reuse. We should also add the OPTIMIZE FOR ALL ROWS clause because our application will fetch and consume all of the query results without waiting. Here is the single SQL statement to do all the work I have described previously:

 

with t1 as

(

select ROW_NUMBER() OVER (PARTITION BY s.studentname ORDER BY a.activity) AS row_num,

s.studentname,

a.activity,

sum(fee) as total_activity_fee

from students s, activities a

where s.studentid = a.studentid

group by s.studentname, a.activity

),

t2 as

(

select ROW_NUMBER() OVER (PARTITION BY s.studentname ORDER BY c.class) AS row_num,

s.studentname,

c.class,

sum(fee) as total_class_fee

from students s, classes c

where s.studentid = c.studentid

group by s.studentname, c.class

),

t3 as

(

select studentname, row_num

from t1

union

select studentname, row_num

from t2

)

select t3.studentname, t1.activity, sum(t1.total_activity_fee) as Total_Activity_Fee, t2.class,

sum(t2.total_class_fee) as Total_Class_Fee

from t3

left outer join t1 on (t3.studentname = t1.studentname AND t3.row_num = t1.row_num)

left outer join t2 on (t3.studentname = t2.studentname AND t3.row_num = t2.row_num)

group by grouping sets (

(t3.studentname, t3.row_num, t1.activity, t2.class),

(t3.studentname),

()

)

order by t3.studentname, t1.activity, t2.class

optimize for all rows;

Now that we have our SQL statement built and tested, let's turn our attention to performance. Using the advanced System i Navigator tools such as Visual Explain, we can see the "out of the box" plan for this query (Figure 8). We can also make use of the index advice provided automatically by DB2 for i.

 

102208CainFigure8.GIF

Figure 8: This is the plan for our query.

 

Focusing on the top, rightmost nodes, we can see that the plan involves full scans on the tables: students, activities, and classes (Figure 9). This makes sense, given there are no local selection predicates for any of the tables. The inner join order is students, then activities and students, and then classes. To accomplish the joins, hash tables are built and probed. This makes sense, given there are no indexes available to facilitate joins by key.

 

102208CainFigure9.GIF

Figure 9: We accomplish the joins by using hash tables.

 

The results of the inner joins are sorted and placed in temporary lists. These sorted lists will be used to support the row-number processing. This is represented by the ranking nodes. The intermediate results are then combined via the UNION (Figure 10).

 

102208CainFigure10.GIF

Figure 10: The intermediate results are combined via the UNION.

 

The results of the UNION operation are then left outer joined on studentname and row_num to the earlier intermediate results (Figure 11). These results are sorted and placed in a temporary list with duplicates removed.

 

102208CainFigure11.GIF

Figure 11: The UNION results are left outer joined on studentname and row_num.


The final, single, sorted list will be used to support the three levels of aggregations specified by the grouping sets. All three totals are calculated with one pass of the data coming from the previous join results (Figure 12). The aggregated results are sorted based on the order by criteria and delivered to the user.

 

102208CainFigure12.GIF

Figure 12: The totals are calculated.

 

To tune up our query, we can take advantage of the DB2 for i index advisor. The indexes being advised can be found in the table QSYS2.SYSIXADV by using the Navigator. In our case, we are invoking the advisor from Visual Explain and can see that three indexes are being suggested:

 

102208CainFigure13.GIF
Figure 13: The index advisor suggests three indexes.

 

To support the joins between students and their classes and activities, we would provide indexes on the respective join columns, such as this:

 

create index students_ix1 on students (studentid);

create index activities_ix1 on activities (studentid);

create index classes_ix1 on classes (studentid);

These indexes will give the DB2 for i query optimizer more information about the data and provide another option for joining the tables--namely, nested loop join by key. Ultimately, the optimizer will choose what it calculated as the fastest plan for your query, against your data, on your system.

 

If for our report we wanted to select only one student, by name, we would modify the query to have a local selection predicate. We should also provide additional indexes to support the local selection-plus-join conditions. Our new SQL request might look like this:

 

with t1 as

(

select ROW_NUMBER() OVER (PARTITION BY s.studentname ORDER BY a.activity) AS row_num,

s.studentname,

a.activity,

sum(fee) as total_activity_fee

from students s, activities a

where s.studentid = a.studentid

group by s.studentname, a.activity

),

t2 as

(

select ROW_NUMBER() OVER (PARTITION BY s.studentname ORDER BY c.class) AS row_num,

s.studentname,

c.class,

sum(fee) as total_class_fee

from students s, classes c

where s.studentid = c.studentid

group by s.studentname, c.class

),

t3 as

(

select studentname, row_num

from t1

union

select studentname, row_num

from t2

)

select t3.studentname, t1.activity, sum(t1.total_activity_fee) as Total_Activity_Fee, t2.class,

sum(t2.total_class_fee) as Total_Class_Fee

from t3

left outer join t1 on (t3.studentname = t1.studentname AND t3.row_num = t1.row_num)

left outer join t2 on (t3.studentname = t2.studentname AND t3.row_num = t2.row_num)

where t3.studentname = 'Mike Cain'

group by grouping sets (

(t3.studentname, t3.row_num, t1.activity, t2.class),

(t3.studentname),

()

)

order by t3.studentname, t1.activity, t2.class

optimize for all rows;

And to avoid full table scans, our supporting indexes would be these:

create index students_ix2 on students (studentname, studentid);

create index activities_ix2 on activities (studentname, studentid);

create index classes_ix2 on classes (studentname, studentid);

For this scenario, it would be perfectly acceptable to have all six indexes in place. These indexes will be available to handle the request for all students, as well as a particular set of students, as specified in the WHERE clause.

 

Furthermore, if this report would be expected to query, process, and return a much larger set of rows, then the optional DB2 Symmetric Multiprocessing feature could be employed to provide parallel processing. This might entail parallel table scans to read the base tables and populate the hash tables, as well as run the joins in parallel. If multiple CPUs and a supporting I/O subsystem were in place, SMP could possibly provide a significant performance increase and lower the response time.

 

As you can see, SQL is a very powerful and robust language. Getting the most benefit out DB2 for i requires keeping the concept of "set at time" in mind and making use of all the latest features and functions. You can use this drill-across technique to handle situations where you need to place related or unrelated figures next to each other horizontally, such as drilling across and combining measures from two or more fact tables by subject.

 

For more information and details regarding the DB2 for i OLAP functions, be sure to review the 6.1 DB2 for i SQL Reference.

Mike Cain

Mike Cain is the team leader of the IBM DB2 for i Center of Excellence in Rochester, Minnesota. He can be reached at mcain@us.ibm.com.

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    Watch security expert Robin Tatam as he discusses a new approach for onboarding new users on IBM i and best-practices techniques for managing and monitoring activities after they sign on.

  • Don't Just Settle for Query/400...

    SB_HelpSystems_WC_GenericWhile introducing Sequel Data Access, we’ll address common frustrations with Query/400, discuss major data access, distribution trends, and more advanced query tools. Plus, you’ll learn how a tool like Sequel lightens IT’s load by:

    - Accessing real-time data, so you can make real-time decisions
    - Providing run-time prompts, so users can help themselves
    - Delivering instant results in Microsoft Excel and PDF, without the wait
    - Automating the query process with on-demand data, dashboards, and scheduled jobs

  • How to Manage Documents the Easy Way

    SB_HelpSystems_WC_GenericWhat happens when your company depends on an outdated document management strategy?
    Everything is harder.
    You don’t need to stick with status quo anymore.
    Watch the webinar to learn how to put effective document management into practice and:

    • Capture documents faster, instead of wasting everyone’s time
    • Manage documents easily, so you can always find them
    • Distribute documents automatically, and move on to the next task

     

  • Lessons Learned from the AS/400 Breach

    SB_PowerTech_WC_GenericGet actionable info to avoid becoming the next cyberattack victim.
    In “Data breach digest—Scenarios from the field,” Verizon documented an AS/400 security breach. Whether you call it AS/400, iSeries, or IBM i, you now have proof that the system has been breached.
    Watch IBM i security expert Robin Tatam give an insightful discussion of the issues surrounding this specific scenario.
    Robin will also draw on his extensive cybersecurity experience to discuss policies, processes, and configuration details that you can implement to help reduce the risk of your system being the next victim of an attack.

  • Overwhelmed by Operating Systems?

    SB_HelpSystems_WC_GenericIn this 30-minute recorded webinar, our experts demonstrate how you can:

    • Manage multiple platforms from a central location
    • View monitoring results in a single pane of glass on your desktop or mobile device
    • Take advantage of best practice, plug-and-play monitoring templates
    • Create rules to automate daily checks across your entire infrastructure
    • Receive notification if something is wrong or about to go wrong

    This presentation includes a live demo of Network Server Suite.

     

  • Real-Time Disk Monitoring with Robot Monitor

    SB_HelpSystems_WC_GenericYou need to know when IBM i disk space starts to disappear and where it has gone before system performance and productivity start to suffer. Our experts will show you how Robot Monitor can help you pinpoint exactly when your auxiliary storage starts to disappear and why, so you can start taking a proactive approach to disk monitoring and analysis. You’ll also get insight into:

    • The main sources of disk consumption
    • How to monitor temporary storage and QTEMP objects in real time
    • How to monitor objects and libraries in real time and near-real time
    • How to track long-term disk trends

     

     

  • Stop Re-keying Data Between IBM I and Other Applications

    SB_HelpSystems_WC_GenericMany business still depend on RPG for their daily business processes and report generation.Wouldn’t it be nice if you could stop re-keying data between IBM i and other applications? Or if you could stop replicating data and start processing orders faster? Or what if you could automatically extract data from existing reports instead of re-keying? It’s all possible. Watch this webinar to learn about:

    • The data dilemma
    • 3 ways to stop re-keying data
    • Data automation in practice

    Plus, see how HelpSystems data automation software will help you stop re-keying data.

     

  • The Top Five RPG Open Access Myths....BUSTED!

    SB_Profound_WC_GenericWhen it comes to IBM Rational Open Access: RPG Edition, there are still many misconceptions - especially where application modernization is concerned!

    In this Webinar, we'll address some of the biggest myths about RPG Open Access, including:

    • Modernizing with RPG OA requires significant changes to the source code
    • The RPG language is outdated and impractical for modernizing applications
    • Modernizing with RPG OA is the equivalent to "screen scraping"

     

  • Time to Remove the Paper from Your Desk and Become More Efficient

    SB_HelpSystems_WC_GenericToo much paper is wasted. Attempts to locate documents in endless filing cabinets.And distributing documents is expensive and takes up far too much time.
    These are just three common reasons why it might be time for your company to implement a paperless document management system.
    Watch the webinar to learn more and discover how easy it can be to:

    • Capture
    • Manage
    • And distribute documents digitally

     

  • IBM i: It’s Not Just AS/400

    SB_HelpSystems_WC_Generic

    IBM’s Steve Will talks AS/400, POWER9, cognitive systems, and everything in between

    Are there still companies that use AS400? Of course!

    IBM i was built on the same foundation.
    Watch this recorded webinar with IBM i Chief Architect Steve Will and IBM Power Champion Tom Huntington to gain a unique perspective on the direction of this platform, including:

    • IBM i development strategies in progress at IBM
    • Ways that Watson will shake hands with IBM i
    • Key takeaways from the AS/400 days

     

  • Ask the RDi Experts

    SB_HelpSystems_WC_GenericWatch this recording where Jim Buck, Susan Gantner, and Charlie Guarino answered your questions, including:

    • What are the “hidden gems” in RDi that can make me more productive?
    • What makes RDi Debug better than the STRDBG green screen debugger?
    • How can RDi help me find out if I’ve tested all lines of a program?
    • What’s the best way to transition from PDM to RDi?
    • How do I convince my long-term developers to use RDi?

    This is a unique, online opportunity to hear how you can get more out of RDi.

     

  • Node.js on IBM i Webinar Series Pt. 2: Setting Up Your Development Tools

    Profound Logic Software, Inc.Have you been wondering about Node.js? Our free Node.js Webinar Series takes you from total beginner to creating a fully-functional IBM i Node.js business application. In Part 2, Brian May teaches you the different tooling options available for writing code, debugging, and using Git for version control. Attend this webinar to learn:

    • Different tools to develop Node.js applications on IBM i
    • Debugging Node.js
    • The basics of Git and tools to help those new to it
    • Using NodeRun.com as a pre-built development environment

     

     

  • Inside the Integrated File System (IFS)

    SB_HelpSystems_WC_GenericDuring this webinar, you’ll learn basic tips, helpful tools, and integrated file system commands—including WRKLNK—for managing your IFS directories and Access Client Solutions (ACS). We’ll answer your most pressing IFS questions, including:

    • What is stored inside my IFS directories?
    • How do I monitor the IFS?
    • How do I replicate the IFS or back it up?
    • How do I secure the IFS?

    Understanding what the integrated file system is and how to work with it must be a critical part of your systems management plans for IBM i.

     

  • Expert Tips for IBM i Security: Beyond the Basics

    SB PowerTech WC GenericIn this session, IBM i security expert Robin Tatam provides a quick recap of IBM i security basics and guides you through some advanced cybersecurity techniques that can help you take data protection to the next level. Robin will cover:

    • Reducing the risk posed by special authorities
    • Establishing object-level security
    • Overseeing user actions and data access

    Don't miss this chance to take your knowledge of IBM i security beyond the basics.

     

     

  • 5 IBM i Security Quick Wins

    SB PowerTech WC GenericIn today’s threat landscape, upper management is laser-focused on cybersecurity. You need to make progress in securing your systems—and make it fast.
    There’s no shortage of actions you could take, but what tactics will actually deliver the results you need? And how can you find a security strategy that fits your budget and time constraints?
    Join top IBM i security expert Robin Tatam as he outlines the five fastest and most impactful changes you can make to strengthen IBM i security this year.
    Your system didn’t become unsecure overnight and you won’t be able to turn it around overnight either. But quick wins are possible with IBM i security, and Robin Tatam will show you how to achieve them.

  • How to Meet the Newest Encryption Requirements on IBM i

    SB PowerTech WC GenericA growing number of compliance mandates require sensitive data to be encrypted. But what kind of encryption solution will satisfy an auditor and how can you implement encryption on IBM i? Watch this on-demand webinar to find out how to meet today’s most common encryption requirements on IBM i. You’ll also learn:

    • Why disk encryption isn’t enough
    • What sets strong encryption apart from other solutions
    • Important considerations before implementing encryption

     

     

  • Security Bulletin: Malware Infection Discovered on IBM i Server!

    SB PowerTech WC GenericMalicious programs can bring entire businesses to their knees—and IBM i shops are not immune. It’s critical to grasp the true impact malware can have on IBM i and the network that connects to it. Attend this webinar to gain a thorough understanding of the relationships between:

    • Viruses, native objects, and the integrated file system (IFS)
    • Power Systems and Windows-based viruses and malware
    • PC-based anti-virus scanning versus native IBM i scanning

    There are a number of ways you can minimize your exposure to viruses. IBM i security expert Sandi Moore explains the facts, including how to ensure you're fully protected and compliant with regulations such as PCI.

     

     

  • Fight Cyber Threats with IBM i Encryption

    SB PowerTech WC GenericCyber attacks often target mission-critical servers, and those attack strategies are constantly changing. To stay on top of these threats, your cybersecurity strategies must evolve, too. In this session, IBM i security expert Robin Tatam provides a quick recap of IBM i security basics and guides you through some advanced cybersecurity techniques that can help you take data protection to the next level. Robin will cover:

    • Reducing the risk posed by special authorities
    • Establishing object-level security
    • Overseeing user actions and data access

     

     

     

  • 10 Practical IBM i Security Tips for Surviving Covid-19 and Working From Home

    SB PowerTech WC GenericNow that many organizations have moved to a work from home model, security concerns have risen.

    During this session Carol Woodbury will discuss the issues that the world is currently seeing such as increased malware attacks and then provide practical actions you can take to both monitor and protect your IBM i during this challenging time.

     

  • How to Transfer IBM i Data to Microsoft Excel

    SB_HelpSystems_WC_Generic3 easy ways to get IBM i data into Excel every time
    There’s an easy, more reliable way to import your IBM i data to Excel? It’s called Sequel. During this webinar, our data access experts demonstrate how you can simplify the process of getting data from multiple sources—including Db2 for i—into Excel. Watch to learn how to:

    • Download your IBM i data to Excel in a single step
    • Deliver data to business users in Excel via email or a scheduled job
    • Access IBM i data directly using the Excel add-in in Sequel

    Make 2020 the year you finally see your data clearly, quickly, and securely. Start by giving business users the ability to access crucial business data from IBM i the way they want it—in Microsoft Excel.

     

     

  • HA Alternatives: MIMIX Is Not Your Only Option on IBM i

    SB_HelpSystems_WC_GenericIn this recorded webinar, our experts introduce you to the new HA transition technology available with our Robot HA software. You’ll learn how to:

    • Transition your rules from MIMIX (if you’re happy with them)
    • Simplify your day-to-day activities around high availability
    • Gain back time in your work week
    • Make your CEO happy about reducing IT costs

    Don’t stick with a legacy high availability solution that makes you uncomfortable when transitioning to something better can be simple, safe, and cost-effective.

     

     

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  • Backup and Recovery on IBM i: Your Strategy for the Unexpected

    SB HelpSystems SC 5413Robot automates the routine tasks of iSeries backup and recovery, saving you time and money and making the process safer and more reliable. Automate your backups with the Robot Backup and Recovery Solution. Key features include:
    - Simplified backup procedures
    - Easy data encryption
    - Save media management
    - Guided restoration
    - Seamless product integration
    Make sure your data survives when catastrophe hits. Try the Robot Backup and Recovery Solution FREE for 30 days.

  • Manage IBM i Messages by Exception with Robot

    SB HelpSystems SC 5413Managing messages on your IBM i can be more than a full-time job if you have to do it manually. How can you be sure you won’t miss important system events?
    Automate your message center with the Robot Message Management Solution. Key features include:
    - Automated message management
    - Tailored notifications and automatic escalation
    - System-wide control of your IBM i partitions
    - Two-way system notifications from your mobile device
    - Seamless product integration
    Try the Robot Message Management Solution FREE for 30 days.

  • Easiest Way to Save Money? Stop Printing IBM i Reports

    SB HelpSystems SC 5413Robot automates report bursting, distribution, bundling, and archiving, and offers secure, selective online report viewing.
    Manage your reports with the Robot Report Management Solution. Key features include:

    - Automated report distribution
    - View online without delay
    - Browser interface to make notes
    - Custom retention capabilities
    - Seamless product integration
    Rerun another report? Never again. Try the Robot Report Management Solution FREE for 30 days.

  • Hassle-Free IBM i Operations around the Clock

    SB HelpSystems SC 5413For over 30 years, Robot has been a leader in systems management for IBM i.
    Manage your job schedule with the Robot Job Scheduling Solution. Key features include:
    - Automated batch, interactive, and cross-platform scheduling
    - Event-driven dependency processing
    - Centralized monitoring and reporting
    - Audit log and ready-to-use reports
    - Seamless product integration
    Scale your software, not your staff. Try the Robot Job Scheduling Solution FREE for 30 days.

  • ACO MONITOR Manages your IBM i 24/7 and Notifies You When Your IBM i Needs Assistance!

    SB DDL Systems 5429More than a paging system - ACO MONITOR is a complete systems management solution for your Power Systems running IBM i. ACO MONITOR manages your Power System 24/7, uses advanced technology (like two-way messaging) to notify on-duty support personnel, and responds to complex problems before they reach critical status.

    ACO MONITOR is proven technology and is capable of processing thousands of mission-critical events daily. The software is pre-configured, easy to install, scalable, and greatly improves data center efficiency.