How to turn your boring work into an amazing experience?

Have you ever found yourself stuck in boring work? Days are passing slow, and you just have no motivation to get up from your bed and go to the office. You find yourself daydreaming, searching the web for your next vacation or even playing an online game. The phenomenon of being bored at work, not enjoying going to the officer and finding millions of excuses to stay home is not new. I read somewhere that around 80% of working people don’t like their job and if they don’t have to do it, they would never do it. 80% of people hating what they do every day is too high of a number. But there is some good news.

Like everyone else, I was stuck in dread boring office work multiple times in my career. I was looking for ways to entertain myself in every possible creative scenario, from having super long breaks to playing every possible online game. I even got bored with the games and news of the web portals that I read every day. Time wasn’t passing fast enough, and I was stuck.

Where to start when things are not going your way anymore?

Make a decision to change the things in your favor by yourself. Get out of your comfort zone.

One day, after long waiting, I decided that I need to take things in my hands. I realized that my manager would never give me the exciting tasks that were nice to have, he needed the operational tasks done. I decided that I realized that the time to stop wasting my life in doing boring and to a significant extent unproductive tasks have come. Just typing what is asked from me to type and live from paycheck to paycheck isn’t my game anymore. I needed a change. And I knew I am that one who is going to bring that change in my work.

I was very aware that the management was really focused on finishing the operational tasks, fast. The business was waiting. So I was okay with the fact that I will have to put some extra hours in creating my own project.

Do ground research before you come up with a plan
The culture in every company is always fantastic if you are open to it.

People love to talk about their work, most of the time they will complain about it, but if you listen carefully enough, you will find the reason what bothers them.

That is why I think that these data scientists need to have some soft skills as I describe in my previous article.

I was already working for 6 months in this specific company. During those 6 months, I tried to meet many of my colleagues that I thought their work is exciting and I can learn from them.

In the beginning, it was a bit strange. According to me, people weren’t accustomed that someone from IT will just walk around the floors of the company and approach them and invite them for lunch. But after a dozen invitations people learned about my friendly and curious nature, so I had an easier time in making invitations. Still, on many occasions, I had to be patient and wait for a free spot on their agenda, or try to find understanding when they cancel on me six times.

In the end, persistence paid off.

In my research time, I managed to talk with my colleagues on different seniority levels from a different department and got really accustomed with the business plan, the business model and more importantly the problems that the business was facing.

Now, that I knew the core of the business, I knew that some exciting opportunities can be tackled and can bring the company on the next level.

The company I worked at that time was into the travel sector. They were selling airplane tickets and travel arrangements.

My professional interest was creating predictive algorithms and work with machine learning. Predictive algorithms can really give benefit to a company in the travel sector. However, in my surprise, predictive algorithms and machine learning weren’t used very much there.

Soon I would discover why.

After work hours I started working on a few project descriptions and use cases that I identified that would be valuable for the company.

I used our data to create working demos and presentations on how the project would help in the long run.

First, I presented this to my manager and his manager, they were both impressed by the ideas. They were pleased to give me permission to continue working on this project as long as I was working on in them after work hours. I was okay with it.

Pitching the projects to stakeholders
Naturally, I started talking with the managers I was close to and slowly started planting my ideas into them for bringing new projects in the company. I would ask them: What do you think if we could do this project to help you with that? Most of the times I would get a positive response, I realized later, more out of courtesy.

I realized, most of the time people want to stay in their comfort zone, protect their position and don’t accept gladly new ideas that might endanger their status or even worse, make them learn something new.
After a month from planting my ideas to different stakeholders, I arranged a meeting where I wanted to present the working demos to them.

On my big surprise, the response I got from them was unexpected. Mostly it was going in the lines of: “I love the idea, but I have more important things on my timeline.” or “I would not change things until they are bringing profit.”, “Excel gives me the forecasts I need, I don’t need anything more than that.”

Stay persistent – Don’t get discouraged easily
These responses were a shock to me, for months I listen people whining about their work, the processes, and faulty systems, but the time I came to them with working solutions, they rejected it immediately saying that they don’t need improvement nor changes.

However, I was determined to upgrade myself and my work, and there was no one stopping me.

Next destination was the 15th floor. 15th floor was reserved for C level people and high management.

I had the opportunity to meet a few of our C level people during company celebrations, and I left space for future unofficial conversation with them.

In my experience, in big companies, you can’t just schedule a meeting with C level person. Especially if you are coming from a low levels hierarchy, like me coming from IT at that time. So you need to make the meeting happen outside their office.

I already knew that the kitchen is the place where everyone must come past by at least once a day. My strategy was to prey on the C level people I had spoken to before and in an informal conversation mention them that I work on this exciting project that can help the business if it implemented.

After patient praying for a few weeks, I managed to meet the CEO of the company in the hallway on his way out. And in time of 6 minutes, the time to go from 15th floor to the parking lot and his car, I managed to tell him the most interesting facts about my projects that he invited me for an official meeting. I was thrilled, my plan was finally working.

The big meeting

After two weeks of meeting my CEO, the big meeting happened.

In those two weeks, I gave the maximum effort to make my demo the most exciting and eye-catching it can be.

The meeting was planned to be only 30 minutes, and it was about to happen not only with the CEO but with other stakeholders that he counted as critical people for the business.

After an hour and a half – one hour after the initially planned meeting, my big rally was over, and I got the attention I needed.

From the following Monday, I officially started working on my project half of the week. I got the promise that if the initial test phase is successful, I would be allowed to work on this full time and even form my own team. I was in the stars.

Not everyone is happy when you progress

My big news wasn’t accepted so gladly from some other managers. Now they started seeing me as their competition. The immediately scheduled meetings on which they tried very hard to prove that my project will fail.

These people were longer in the company, they already knew the business more than I do and their name was recognized more than mine was. All this made me sweat profoundly before and during the meetings, but also made me make sure that my demo is bulletproof and covered from every possible angle.

Nevertheless, I showed that I’m not bothered by their attitude and I kept the most friendly and professional character.

In the end, the only thing that matters is your goal

After a painful but exciting test phase, the final results were out. The predictive model turned out to be even more successful in the real world scenario, and the business owners were really pleased with the extra profit that the project brought.

Now I had the opportunity to work my dream work and never get bored from it again.

All the difficulties during the process, after work hours, unpleasant moments and failures now seemed like nothing else but a good experience, because all it matters is: I realized my plan.

 

Web Analytics – Why is SEO important?

This is guest article written by Sr Data Science Manager, Brand and Advertising, Kire Hajba.
Follow him on LinkedIn

Building a strong brand in today’s word is a real challenge. The web, the globalization, the widespread knowledge, the easily accessible information and lot more is expanding the competition from your neighborhood to the whole wide world.
This highly competitive environment puts high standards for the success of the business. Building a website with a nice graphic is not a fancy feature anymore, but a standard. However, the fancy website will mean nothing to your business without the well-expected visitors.
There are millions of websites out there so standing in front of the crowd is not easy, at least not without good SEO

SEO or Search Engine Optimization is a methodology of strategies, techniques, and tactics used to optimize your website in order to increase the number of organic visitors to your website.

Organic visitors, what are those?

Those are all people who found you by executing a search query on some search engine like Google, Bing or Yahoo. This traffic is the one that all marketers strive to increase. Important to note here is that these visitors are free and they are very valuable since they came in your website considering the information presented as very valuable, thus the possibility for high conversion rate.

 The free and valuable new visitors are not the only pros when you think of SEO. SEO can also save lots of money from your company. Think of all AdWord campaigns and all of the money spent in order to show your website on specific keywords. All those money could have helped you with the creation of amazing and fun content for your visitors making sure your visitors have bookmarked your website and they are happily coming back to your website and checking all new fun things happening around.

Good content is not making only your visitors happy but the search engines too! All good content is increasing the Page Authority of your website making it more relevant for the search engine, directly increasing your chance to show higher in front of your competitors.

But wait, there is more!

The relevancy of your website is directly influencing the money spent on all AdWords campaigns. The method of calculating the price of your AdWord campaign is not trivial and includes lots of factors, however, one factor is something you can control: The Quality Score.

What is Quality Score?

Quality Score is Google’s rating of the quality and relevance of both, your keywords and PPC add.   

Your Quality Score depends on multiple factors, including:

•    Your click-through rate (CTR).

•    The relevance of each keyword to its ad group.

•    Landing page quality and relevance.

•    The relevance of your ad text.

•    Your historical AdWords account performance.

In short words, higher quality score = lower cost per conversion. The better you are in meeting your prospects needs, the less will Google charge you for the ad click:

 In the upcoming series for SEO, we will cover how to increase the Quality Score and how to get more for less.
 Stay tuned for more!

OLAP in the Big Data world

In the previous months, I have been thinking is OLAP dead technology or we can still find the use of it?

OLAP Over Hadoop

In the last few years, Hadoop has really come forward as a massively scalable distributed computing platform. Most of us are aware that it uses Map Reduce Jobs to perform computation over Big Data which is mostly unstructured. Of course, such a platform cannot be compared with a relational database storing structured data with a defined schema. While Hadoop allows you to perform Deep analytics with complex computations, when it comes to performing multidimensional analytics over data Hadoop seems lagging. You might argue that Hadoop was not even built for such uses. But when the users start putting their historical data in Hadoop they also start expecting multidimensional analytics over it in real time. Here “real time” is really important.

Some of you might think that you can define OLAP friendly Warehousing Star Schema using Hive for your data in Hadoop and use a ROLAP tool. But there comes the catch. Even on the partially aggregated data, the ROLAP queries will be too slow to make it real-time OLAP. As Hive structures the data at reading time, the fixed initial time is taken for each Hive query makes Hadoop really unusable for real-time multidimensional analytics.

The only options left to you are either you aggregate the data in Hadoop and bring the partially aggregated data in an RDBMS. Thus you can use any standard OLAP tool to connect to your RDBMS and perform Multidimensional analytics using ROLAP or MOLAP. While ROLAP will directly fire the queries against the Database, MOLAP will further summarize and aggregate the multidimensional data in the form of cuboids for a cube.

The other option is you use a MOLAP tool that can compute the aggregates for the data in Hadoop and get the computed cube locally. This will allow you to do a really real-time OLAP. Moreover, if the aggregates can be performed in Hadoop itself that will really make cube computations scalable and fast.

There can be a big fight over the point that Hadoop is not a DBMS but when Hadoop reaches to users and organizations who look to use it just because it is a buzzword, they expect almost anything out of it that a DBMS can do. You should see such solutions growing in the near future.

 Just like with data warehouses, analytics software has been around for some time and has been providing value to business users for many years around problem domains such as market basket analytics, sales analytics, predictive analytics, etc.
Now we can see a lot of current advertising and buzz around “Big Data Analytics”. So what makes your analytics “Big Data Analytics”?
Is it adding OLAP/MDX layers on top of Hadoop and NoSQL databases? Or can we call our analytics Big Data Analytics if we ETL data from HDFS with tools like Sqoop, SSIS or Kettle into a traditional RDBMS into a star schema? Based on feedback from my post called “Did Big Data Kill OLAP Cubes“, my guess would be that most of you do not think that is sufficient.
But what about scale & performance as part of the Big Data equation? You know: the volume, velocity, variety, etc … Does traditional OLAP on top of those sources provide the analytics that a data scientist requires?
A very important aspect to Big Data Analytics that differentiates from traditional BI analytics (this is my PM opinion!) is the target persona. Big Data Analytics is primarily for data scientists vs. knowledge workers and business decision makers. Data scientists can subsequently work with IT on a process to “operationalize” their data discovery and outputs from their models such that traditional BI solutions can consume their processed data.
So if you buy into this definition of Big Data Analytics, what this means is that you will need:
  1. Big Data scale with distributed analytics processed with data locality on cluster data nodes
  2. In-memory data caching for quick response times from interactive tools
  3. Columnar compression in order to fit large data sets in memory
  4. Data mining algorithms
  5. Data visualization tools that encourage data discovery, anomaly detection, and data blending

SQL Service fails to start with error code 126

  1. Start->All Programs -> Microsoft Sql server 2005 -> Configuration Tools -> SQL Server Configuration Manager. 
  2. In the SQL SERVER configuration Manager Window, click the plus (+) sign against SQL SERVER 2008 Network Configuration. 
  3. Highlight ‘Protocols for MS SQL SERVER’ In the right pane 
  4. Right click the VIA protocol
  5. select ‘Disable’ 
  6. Then try to start the service.

Get the connection back when your database is stuck in single mode

For some reason you put your database in SINGLE_MODE.


ALTER DATABASE fbDataCollector SET  SINGLE_USER WITH ROLLBACK IMMEDIATE
GO

After a while you realised that you can not bring it back in MULTY_USER because you have been locked out of your DB.

One option is to find the SPID who is using it, kill it and then bring it back to multy_user.

  use master
GO
— the following query lists all database sessions
select d.name, d.dbid, spid, login_time, nt_domain, nt_username, loginame
from sysprocesses p inner join sysdatabases d on p.dbid = d.dbid
where d.name = ‘DBNAME’
GO
— kill session using SPID number
kill 52
GO
exec sp_dboption ‘DBNAME’, ‘single user’, ‘FALSE’

GO

Bu, for some reason this option didnt worked today. After some time in agony, i find another option that actually worked, and it always works, altho it is not as fast as the first one.

The solution is simple. You will try to acces your database by bruteforce.



USE DB_NAME;

GO 1000
This will try to conect to your DB for 1000 times.
You will recive a lot of errors that your DB is in single mode, but after couple of hundreds you will suceed to get the session.
After you do, bring you database into MULTY_USER state with executing the following:

ALTER DATABASE DB_NAME SET MULTI_USER;