Greetings from Dataspace! First of all, we here at Dataspace hope that you and all of your loved ones are safe and well in this time of uncertainty, and that we’ll all soon be back on our feet. As the nation’s workers struggle with unemployment or adjust to working from home, it has become even […]
Tools and techniques for management reporting and analysis have evolved since computers first came out. One can argue that the first management reporting tool was COBOL (COmmon Business Oriented Language). It allowed business people to get data out of systems created by computer people. COBOL was eventually replaced for reporting by tools like Information Builders […]
As you may know, many big data technologies are defined as schema on read. What this means is that you can throw whatever you want on the disk and then, when you need the data, you tell the data store what that data means (e.g. the second column contains price per unit). Traditional relational databases, […]
In the distant past (circa 2015), IT was responsible for providing data consumers with data, tools, and development expertise. Today, the landscape is shifting, especially in larger organizations. Nowadays, IT provides some of the data – the certified, clean data. Consuming departments fill the rest of the needs – tools, analytic experts, even non-certified data. […]
What is Hashing? Hashing is simply passing some data through a formula that produces a result, called a hash. That hash is usually a string of characters and the hashes generated by a formula are always the same length, regardless of how much data you feed into it. For example, the MD5 formula always […]
Predictive analytics is this super-complex field that only statisticians and data scientists can understand, right? Well, perhaps it takes some training to do it well but it only takes two sentences to understand what it’s all about: In predictive analytics we determine the likelihood of something by looking at data about it. We do this simply […]
Number One in Dataspace’s Data Science Series: What does it mean? If nothing else, the data science industry is good at coming up with new, unique, confusing names and terms. ZooKeeper, MapReduce, Hadoop, Pig, Storm, Mahout MongoDB…the list keeps growing and it’s totally understandable if you can’t always identify or explain the different technologies […]
It’s that time of year again! With budgeting for 2018 at the forefront of your agenda, you may be wondering where to head with your data science efforts. Investments in big data are often expensive, but when planned correctly you can manage costs and also ensure that your new systems and employees generate data-driven profits. […]
If you have huge volumes of data, chances are that you can get value out of analyzing that data. But, would you derive significant value from analyzing it in real time? This is an important question because, while there are benefits to real time analytics, there are also real costs. To help you decide whether […]
If you’re like me, you’re an exceedingly attractive, 50-something data geek with a love for aviation history who’s an amazing ice hockey player. You also spend a lot of lunches eating a sandwich while studying new technologies. This kind of on-the-cheap, self service training helps you keep up with changes in business intelligence / data warehousing / analytics / […]
Dataspace Newsletter: Flattening the (other) curveApril 7, 2020 - 2:52 pm
Data science contractors – demand will increase in 2020December 27, 2019 - 3:56 pm
Data Science Salaries in HealthcareOctober 16, 2019 - 1:14 pm
Dataspace to sponsor 2019 Indy Big Data Conference in IndianapolisAugust 22, 2019 - 4:46 pmA Big Mistake Data Science Recruiters MakeJuly 18, 2019 - 3:08 pm
Dataspace featured in Dice article about hiring better data scientistsMay 24, 2019 - 4:24 pm