first_imgTigers host Mosinee on FridayBy Paul LeckerSports ReporterMARSHFIELD — Stevens Point held Marshfield to four hits, and the Tigers left seven runners on base as they fell to the Panthers 4-1 in the Wisconsin Valley Conference softball opener for both teams.Emily Draeger knocked in Jenna Jakobi for Marshfield’s only run in the loss.Draeger, Jakobi, Megan Nordbeck, and Jordan Pretsch each had one hit for the Tigers.Megan Donahue gave up two earned runs and struck out eight in a complete-game effort for Marshfield. She allowed seven hits and three walks.Stevens Point (1-0) statistics were not provided.Marshfield (1-1) returns to action Friday, hosting Mosinee in a nonconference game at 4:30 p.m. at the Marshfield Fairgrounds.(Hub City Times Sports Reporter Paul Lecker is also the publisher of MarshfieldAreaSports.com.)last_img read more

first_imgDingaan Thobela established himself as a charismatic, gifted fighter and a favourite of the South African public.Former boxing champion Dingaan Thobela is known as “The Rose of Soweto”.(Image: Cara Viereckl, via IOL)Brand South Africa reporterDingaan Thobela has proved himself as one of South Africa’s most talented boxers, although perhaps not the most hardworking fighter. The charismatic Thobela started his professional career in 1986 as a junior welterweight, but has since moved up to the light heavyweight ranks – representing a rise of almost 16 kilograms.He has even spoken of possibly campaigning as a heavyweight whether he was serious or not remains to be seen.After an amateur career that saw him win 80 times and lose just three bouts, Thobela’s first professional fight pitted him against Quinton Ryan, a bout he won in four rounds. The slick-punching Thobela was held to a draw in his fourth fight, but proceeded to win 25 fights in a row over the next five years, registering 19 wins by knockout along the way.Dingaan Thobela starts his professional career in 1986 as a junior welterweight, but later moved up to the light heavyweight ranks – representing a rise of almost 16 kilograms. (Image: African Ring)Fighting outside South AfricaAs he scored more and more wins, Thobela became increasingly marketable and began to fight outside of South Africa. In 1990, three of his five fights were in the United States and all three ended in victories, two by knockout over Pascual Aranda and Mauricio Aceves who he both disposed of in the fifth round.In 1991, Thobela’s three contests were all won on points, and in 1992 he fought only twice, defeating Tony Foster over eight rounds and stopping Peter Till in nine rounds.At the beginning of February 1993, “The Rose of Soweto” took on Tony Lopez for the WBA lightweight title. Lopez had previously fought twice against South African boxing legend Brian Mitchell. Mitchell, who retired as WBA champion after 13 successful title defences, had fought Lopez in Sacramento on both occasions. The first bout ended in a controversial draw and Mitchell left the matter in no doubt the second time around.Controversial lossThobela discovered how difficult it was to win in Lopez’ backyard when he lost on a controversial points decision. Four months later he faced Lopez at Sun City, and this time he captured the title.Thobela made his first defence in October, but came up against a superior fighter in the unbeaten Orzubek Nazarov, who claimed a convincing 12-round decision. Thobela challenged for the title again in March 1994, but Nazarov had his number and won over 12 rounds in a repeat of his previous victory. Later in the year Thobela faced journeyman Karl Taylor in England and was surprisingly knocked out in the eighth round of their contest.In 1995 Thobela got back on track with five victories, all of them by knockout, and added a further two KO victories by June 1996. However, matters went haywire again for “The Rose” when he faced Geoff McCreesh in November. McCreesh, who came into the fight with a record of 15 wins and three losses, mostly against little-known British opponents, stunned Thobela in the second round, sending the South African to the canvas for a huge upset victory.Beaten by a journeymanIn his next fight, in March 1997, Thobela was beaten by American journeyman Willy Wise, who came into the fight with 21 wins – only six by knockout – three losses and four draws. The South African was favoured to win, but Wise secured a points victory.Questions were being asked about Thobela’s commitment, but he secured a big win later in the year, defeating fellow South African Gary Murray on a fourth-round TKO. In 1998 he fought only once, drawing against Carlos Baldomir over 12 rounds. Thobela looked rusty and out of shape and doubts grew about his boxing career.However, he returned for two fights in 1999. He won in seven rounds against Walter Danett, but was beaten on points by Cornelius Carr for the WBF middleweight title.World title winIn early 2000 he won a points decision over Soon Botes to earn a crack at Glen Catley’s WBC super middleweight title. The Briton was heavily favoured to retain his crown, but Thobela, way behind on all three judges’ scorecards, staged a strong finish, dramatically knocking Catley out with only seconds remaining in the bout. He was once again a world champion.As had happened previously, Thobela was unable to defend his world title, losing to Canada’s Dave Hilton on a controversial points decision in Montreal. Shortly afterwards, Hilton was jailed for rape and Thobela was given another crack at the title against Eric Lucas in November 2001. He struggled to make the weight, however, and Lucas dominated the fight before winning on a TKO in the eighth round.Thobela was a natural: a gifted boxer who, at the the height of his career, established himself as a charismatic, gifted fighter and a favourite of the South African public.Would you like to use this article in your publication or on your website? See Using Brand South Africa material.last_img read more

first_imgCustomers. Do you know who your customer is? I do. I know my target market and can define my customer. I’m not marketing to everyone. Who are the companies you are marketing to, the people who will be most receptive to your messages, and how will you serve them? What are their ages, desires, needs and pain points?All this data will help you create an impressive resume. But they’re also the statistics you should know today, whether you’re walking into a meeting or sitting down with your boss to evaluate your progress or justify a budget increase.Before you use this data to polish up your resume, think about how you can put that data to work every day on the job.3 tools to organize your data for success1. A monster dashboardIf you aren’t an Excel expert, become one. My master spreadsheet has 40 different tabs in it. Get to know your dashboard reporting tool, whether you use Salesforce or a CRM or an e-commerce tool. Be the expert in pulling the essential data. Carry that data into your meetings and update it regularly.The dashboard will help you focus on what’s important and what you need to know. Talk to other people in your organization if you need to fill in blanks.2. DIY metricsYour dashboard should show your organization’s KPIs, such as the percentage of leads converted to purchase, but you also need your own set of metrics that show your email success on your own terms.Statistics like time to purchase, subscriber/customer lifetime or percentage of quality leads might not be important to your executives, but you need them to be a good marketer.If your dashboard doesn’t give you those metrics, then create your own.That’s what I ended up doing earlier in my career because I wasn’t getting the numbers I needed to show how my programs were succeeding. I ended up with 15 pages of numbers that tracked different pieces of the business. I took them into every meeting and was able to rattle them off from memory because I knew the numbers intimately.3. StorytellingThe best job candidates I interviewed told compelling stories. If you want to advocate more effectively for your email program, you will know your story inside and out and tell it in ways that your audience will understand.Knowing your story will help you clarify what you send prospects, subscribers and customers. You also must know how to tailor your story for different audiences. This is crucial if you’re introducing your brand to a new audience, as I did when I brought a UK brand into the US market.Note: Update your story daily. Telling the same story over and over makes it go stale. Update it regularly with fresh data. It might take you 25 minutes to write your story but four days to tweak it.The power of knowing your numbers is important, especially in larger organizations. I learned this the day my boss asked me for some numbers that I didn’t have at my fingertips. He said something I never forgot:“If you don’t know these numbers, who does? Because that’s who I want to talk to.”Wrapping upAs an email marketer, you are your own CEO, CFO, COO and front-line person. Act like it. Know your data and use it to create a compelling story. Craft a version of it so that you have an answer the next time someone says, “How’s our email program doing?”The post The business stats you must have on instant recall appeared first on Marketing Land.From our sponsors: The business stats you must have on instant recall After re-entering the job market recently, updating my resume was one of the first things I did. I am a numbers guy, so I started thinking about the metrics that would best highlight my accomplishments.Which KPIs would impress my industry and the top decision-makers in it? What statistics did I use every day on the job?See, I wasn’t just a pretty face on the speaker’s platform at marketing conferences. I headed up US marketing operations for a UK-based email service provider. I carried metrics like these, and many more, into team and client meetings and executive sessions and used them to build out my marketing plans.Then, as I compiled my stats, I had an epiphany.I realized that these big-picture stats aren’t just for your resume. These are the numbers you should be carrying around in your head every day on the job. They’re the stats that help you demonstrate the value and effectiveness of your email program.If someone — like your CEO — were to stop you in the hall and ask, “How’s our email program really doing?” would you have a ready answer? Or would you stumble over a vague statement about open rates and opt-ins?Everyday statistics to carry around in your headThese stats serve me well, both on the job and when I’m summing up my career highlights to date:Testing. In my previous job, we did a lot of cool things to inform our account-based management using test data to inform the ads we showed our prospects so that we could better drive them to our web pages to capture their information. Engagement. What drives engagement? I know which subject lines got the most opens and which emails drove the most clicks. Email success is about more than opens and a good marketer knows what persuades people to open and engage. Best and worst campaigns. You know your victories, but talk about your flops, too. Everybody has them. Show what you learned from your failure and how you avoided repeating it. For me, it was a $10,000 campaign with a new ad tech company. It failed miserably, but I stopped the campaign before I spent all the company’s money. Posted on 4th August 2018Digital Marketing FacebookshareTwittertweetGoogle+share The business stats you must have on instant recallYou are here: KPIs. When I’m on the job, our net sales and opportunity value are constantly in my head. Things like open rates, click rates, conversion rates, number of segments and average order value. What were my goals and what percentage of them did I accomplish? Retention. How did I retain those prospects, customers or subscribers? What are my retention rates quarterly or over a year? What’s the average retention or burnout in the same period? When did I know it was time to stop marketing to a prospect? HomeDigital MarketingThe business stats you must have on instant recall Acquisition. As a B2B marketer, I need to show how many high-quality leads and customers I acquired. For B2C marketers, how many subscribers or customers did you acquire each month? How many converted to purchase in the first 15 or 30 days? What are your lows, highs and averages? Related postsLytics now integrates with Google Marketing Platform to enable customer data-informed campaigns14th December 2019The California Consumer Privacy Act goes live in a few short weeks — Are you ready?14th December 2019ML 2019121313th December 2019Global email benchmark report finds email isn’t dead – it’s essential13th December 20192019 benchmark report: brand vs. non-brand traffic in Google Shopping12th December 2019Keep your LinkedIn advertising strategy focused in 202012th December 2019last_img read more

first_imgIn Pt1 of this blog post I looked at a SQL Query and data set to run in Hadoop and in Pt2 wrote the Map function to extract the relevant fields from the data set to satisfy the query. At this point however we still have not implemented any of the aggregate functions and still have a large key and value intermediate data set. The only data eliminated so far has been the lines examined where the date was not less than or equal to 11-AUG-98. On the test data set out of the initial 600037902 lines of data we now have 586996074 lines remaining, to complete the query we now need to write the reduce phase. The Reduce method will extend the Reducer class. This needs to accept the intermediate key value pairs output by the mapper and therefore will receive as input the key which is fields 9 and 10  concatenated and the DoubleArrayWritable containing the values. For every key we need to iterate through the values and calcuate the totals required for the SUM(), AVG() and COUNT() functions. Once these have been calculated we can format the output as text to be written to a file that will give us exactly the same result as if the query had been processed by a relational database. This reduce phase will look something as follows by simply adding all of the values in the array for the SUM() functions and then dividing by the COUNT() value to calculate the result of the AVG() functions.nfor (DoubleArrayWritable val : values) {x = (DoubleWritable[]) val.toArray();sum_qty += x[0].get();sum_base_price += x[1].get();sum_discount += x[2].get();count_star += x[3].get();sum_disc_price += x[4].get();sum_charge += x[5].get();        }avg_qty = sum_qty/count_star;avg_price = sum_base_price/count_star;avg_disc = sum_discount/count_star;/* Format and collect the output */Text tpchq1redval = new Text(” “+sum_qty+” “+sum_base_price+” “+sum_disc_price+” “+sum_charge+” “+avg_qty+” “+avg_price+” “+avg_disc+” “+count_star);       context.write(key, tpchq1redval);       }  }nCoupled with the Map phase and a Job Control section (this will be covered in the next post on running the job) this Job is now ready to run. However as we have noted previously just for our 100GB data set the map phase will output over 58 million lines of data which will involve a lot of network traffic and disk writes. We can make this more efficient by writing a Combiner.The Combiner also extends the Reducer and in simple cases but not all (as we will cover in a moment) can be exactly the same as the Reducer. The aim of the combiner is to perform a Reducer type operation on the subset of data produced by each Mapper which will then minimise the amount of data that needs to be transferred throughout the cluster from Map to Reduce. The single most important thing about the Combiner is that there is no certainty that it will run. It is available as an optimization but for a particular Map output it might not run at all and there is no way to force it to run. From a development perspective this has important consequences, you should be able to comment out the line in the Job Control section that calls the Combiner and the result produced by the MapReduce Job stays exactly the same. Additionally the input fields for the Combiner must be exactly the same as expected by the Reducer to operate on the Map output and the Combiner output must also correspond to the input expected by the Reducer.  If you Combiner does not adhere to these restrictions your job may compile and run and you will not receive an error, however if not implemented correctly your results may change on each run from additional factors such as changing the imput block size. Finally the Combiner operation must be both commutative and associative. In other words the Combiner operation must ensure that both changing the order of the operands as well as the grouping of the operations you perform does not change the result. In our example the SUM() function is both commutative and associative, the numbers can be summed in any order and we can perform the sum operation on different groups and the result will always remain the same. AVG() on the other hand is commutative but not associative. We can calculate the average with the input data in any order, however we cannot take an average of smaller groups of values and then take the average of this intermediate data and expect the result to be the same. For this reason the Combiner can perform the SUM() operation but not the AVG() and can look as follows producing the intermediate sum values only for the Reducer.nfor (DoubleArrayWritable val : values) { x = (DoubleWritable[]) val.toArray();sum_qty += x[0].get();sum_base_price += x[1].get();sum_discount += x[2].get();count_star += x[3].get();sum_disc_price += x[4].get();sum_charge += x[5].get();  }outArray[0] = new DoubleWritable(sum_qty); outArray[1] = new DoubleWritable(sum_base_price); outArray[2] = new DoubleWritable(sum_discount); outArray[3] = new DoubleWritable(count_star); outArray[4] = new DoubleWritable(sum_disc_price);outArray[5] = new DoubleWritable(sum_charge);DoubleArrayWritable da = new DoubleArrayWritable();da.set(outArray);context.write(key, da);     }  nAt this stage we have written the Mapper, Reducer and Combiner and in Pt4 will look at adding the Job Control section to produce the completed MapReduce job. We will then consider compiling and running the job and tuning for performance.last_img read more