Monthly Archives: February 2014

A Beginner’s Guide to Twitter, 2014

According to Sandy Carter of IBM, 77% of Fortune 500 companies are on social media in some form, whether just to listen, or getting their feet wet. If you’re not on board, you’re getting left behind. When you bring up social media, people-in-the-know keep mentioning Twitter, and you’re not sure why – what makes Twitter different from Facebook?

When people start considering social media for their business, they tend to have at least some familiarity with Facebook, which is generally about connecting with people you already know. On Twitter, that’s a good starting point. But Twitter is more useful for connecting with people you may not already know personally, but share common interests with.

On social media, your username is your brand. If you’re creating a Twitter account specifically for your business, use the name of your business. If you’re creating a Twitter account for your professional self, use your name. Sometimes, though, you may find that you’re unable to do this – your name may be too long (more than 15 characters), or it’s a popular name that’s already been taken. In this case, consider variations that incorporate useful information. Include your industry: Andrew Borg of e3C Consulting, a mobility consultant, goes by @TheMobileBorg on Twitter. (@andrewborg is a different person.) Another example would be to include your business’ location, such as @ArtBarCambridge for the ArtBar restaurant in Cambridge. (@ArtBar belongs to an unrelated person.)

Fill out your bio and add a userpic. If your profile looks incomplete, especially if it still has that egg picture, people tend to not take you seriously (at best), or assume you’re a spammer (at worst). With a business account, use your corporate logo; for a personal account, a headshot is fine. Don’t forget to customize your profile design to coordinate with any existing websites for your business. And send out that first “Hello, world!” tweet! You’re here to engage.

Follow your colleagues and others in your industry, including competitors. At IBM’s recent Entrepreneur Day in Cambridge, Bobbie Carlton of Mass Innovation Nights put it this way: “Where is your audience? Where are your influencers?” I would add: where are your peers? Following others is key; when you don’t, you’re perceived as being on social media solely to broadcast announcements, not to have conversations. That’s not what social media is best used for, and others will think you’re out of touch. On Twitter, you can follow and reply to anyone you’d like. This is a great way to keep up with current discussions and breaking news in your industry, as well as networking and starting conversations with people who share your interests. It’s fairly common now for people to even list their Twitter accounts on their business cards; you can look at their tweets before deciding to follow them. At DataHive Consulting, we put our Twitter usernames on our business cards, as seen below:

Business Cards

Share relevant things that you create. Whether that’s blog posts, software, pottery (assuming you run a pottery business), you can share links and images and video of these things. Even short-form thoughts can be conversation starters. If you’ve got a sneak preview for an upcoming project, share it and get feedback. If you want to offer a discount on something you’re selling, share that! Something special on tonight’s menu at your food truck or restaurant? Share a picture and get hungry people lining up to eat it.

Share relevant things that others create. One of the people you follow wrote a really thought-provoking blog post about an issue in your industry. Tweet about it! Somebody made a tool that’s changed your everyday workflow for the better. Tweet about it and tell people why. Your colleague tweeted something smart and succinct. Retweet it!

Keep up with your interactions and mentions.. In the “Connect” tab of your Twitter account, you can see replies to your tweets, as well as tweets that mention you; who has starred a specific tweet of yours as a “favorite;” and who has retweeted one of your tweets. Also, you can use Twitter’s search function to find out who’s talking about you or your business that might not necessarily know you have a Twitter handle. All of these are invitations to further conversation with these people – strike while the iron is hot! Being responsive to people who’ve shown an interest in you on Twitter encourages them to connect further with you.

Use hashtags properly. Hashtags are a powerful tool. They assign a label to a specific tweet, which makes it easier to find in Twitter search. A hashtag can be as generic as #socialmedia, or as specific as #datastorm14. At conferences or in webinars, the organizer will often suggest that you tweet using a specific hashtag. You can use tools like TweetChat and Twubs to track the hashtag of your choice in a chatroom-like environment with near-realtime updates.

Sort who you follow on Twitter into lists. Once you’re following a number of people, it can feel like you’re trying to drink from a firehose just to keep up. Lists can help filter who you follow into useful categories – a list of your webdev compatriots, a list of your information architecture colleagues, a list of all the Twitter accounts of the software you use. This filtering makes it easier to focus on one subject at a time.

Use Twitter on the go. 75% of Twitter users visit Twitter via a mobile device. Download a Twitter app to your phone, whether the official one, or a third-party offering like Tweetbot or Hootsuite. Check up on your replies or mentions in a quiet moment and respond, or just see what people are talking about. You can fit Twitter into interstitial moments without being tied to your laptop! Just be consistent – check in for a few minutes every day.

So that’s our beginner’s guide to using Twitter. Once you’ve mastered these tips, there’s a world of useful tools beyond the basic Twitter website and mobile app: third-party clients that enable more advanced actions like scheduling tweets, analyzing social data, and better brand and hashtag tracking, among dozens of other use cases. We cover some of this in our Social Media Primer series. If you’d like to learn best practices for using these tools, or have further questions, please contact us at to schedule a free consultation.

What Big Data can learn from the NBA

94Fifty smart sensor basketball photo courtesy 94Fifty.

On Thursday, February 13, Grantland’s Zach Lowe wrote an article on the latest technological development in professional basketball: measuring biometric information in game settings. Four D-League (the NBA’s developmental league) teams will start using one ounce sensors fitted on player jerseys to start measuring metrics such as heart rate speed, and position. These sensors are currently available from one of three companies: STAT Sport, Zephyr, and Catapult. These sensors are not new to professional basketball, as nearly two-dozen NBA teams already use these devices. However, NBA teams currently only use these sensors in practice settings, rather than in game-time situations.

There are a couple of interesting Social Big Data lessons that professional basketball could potentially learn from this experiment that every Big Data expert should be interested in finding out.

First, consider one of the quotes from the Grantland article:

“As the research-and-development arm of the NBA, the NBA D-League is the perfect place to unveil innovative performance analytic devices in-game,” said NBA D-League president Dan Reed.

This concept of an R&D product where you collect more data in an experimental setting is one that many technology companies could start to use. For instance, does your core cash cow product have a corresponding R&D product that can be tinkered with without affecting your revenue? This is a good role for your freemium or single user product. (Heck, Facebook does this for their core platform, although DataHive does not recommend the level of iteration that Facebook provides unless you have a monopoly or duopoly of your core market.) This new use of heart rate and other physical information will provide insights on team tactics and performance if used correctly, thus leading to not just Big Data, but interactive and social Big Data where each player’s metrics are dependent on each other.

Second, and more interestingly from a tactical perspective, this measurement will allow basketball teams to more closely align physical effort with results. It is easy to simply believe that hustle and effort lead to better results, but these metrics may actually show that a lack of hustle could be one of several things. It could be a health issue or laziness or it could be good strategy in saving energy for key moments. Hustle and physical movement should not be measured in isolation, but in context of results. If a “clutch” player ends up moving less than an average player or saves exertion for peak moments, the economics of movement may actually state that excessive “hustle” is detrimental to performance. These sensors may also show that specific team tactics lead to greater efficiency, just as our analysis of shot taking shows how important it currently is to take shots from within 4 feet of the rim or on the sides of the three point line.

From a business perspective, most of us do not put out the physical effort of a professional athlete for a prolonged basis at work. But do we waste time and energy by going in the wrong direction? Are we getting stressed because our managers are not telling us the right information? There is a key challenge of understanding how to use this information productively rather than punitively. It can be easy to fall into the trap of simply stating that more time at work equates to greater productivity, but it may actually be that after a certain point, the error rate or lack of clear thinking outweighs the incremental productivity that would be expected. Follow the real business metrics rather than pure resource utilization.

However, as this occurs, one of the biggest challenges will be to translate sports analytics to business analytics. Keeping score is very easy in a rule-based sports environment, but more difficult in a business environment when it can often be difficult to define KPIs. Based on personal experience and interviews with multiple basketball analysts, DataHive has found that the academics and number crunchers conducting this analysis are largely unaware of the value that these findings could provide in the sports world. Although business analysts can quickly see how the heat and activity maps associated with basketball could translate into greater retail, field, and manufacturing success, one of the great challenges is that the sports analysts currently doing this work do not understand how their work could be translated to other fields. In our role of supporting Social Big Data for Human Insight, DataHive serves as a Sports Data Whisperer that wrangles the findings and techniques used in the sports world and brings them to the business world.

DataHive’s principals have long believed that the structured world of sports serves as a natural testing ground for the predictive, geolocated, and biometric data that is being introduced to the corporate world. Video feed metadata and sensor-based data are the Next Big Things in Big Data and it is only a matter of time before the corporate world follows suit. Regardless of your personal interest in sports, Big Data professionals should keep track of the surveillance and sensor data being used in the basketball world to see how this controlled setting provides potential insight for future enterprise technology efforts.

Defining Social Big Data for Human Insight

Social Big Data for Human Insight
Internet map 1024 by The Opte Project is licensed under CC BY 2.5.

DataHive Consulting is focused on the concept of Social Big Data for Human Insight. But what does that actually mean? For us, there are three key components to this phrase: Social, Big Data, Human Insight.

“Social” is about the engagements and transactions that we use to interact with each other. Social media and social networking are the most obvious examples, but we are interested in the entire span of interactions. Email is a social interaction. Telephony call detail records and text messages are also social interactions. Even our interactions with locations and content can potentially be social if two or more people are interacting with the same location. In short, we are focused on personal and shared interactions.

The most important aspect of “social” is in getting good data. In this case, good data is determined by the quality of interaction. Social data will not be useful if employees, customers, and partners are not interacting with each other and getting value. So, from this perspective, the lessons of effective social collaboration are vitally important for maximizing the value of Social Big Data. Garbage in, garbage out is just as true for relationships as it is for data. Because of this, we care about setting up social engagements properly to create business value and to support ongoing social insight through Social Big Data for Human Insight.

“Big Data” is a bit of a marketing play, to be perfectly honest. We do care about the 3 Vs of Variety, Velocity, and Volume, and we work with video, sentiment analysis, predictive analytics, and data mining. But we also deal with the traditional data management and business intelligence tools that can analyze social data. Often, the key to unlocking the value of social data is as simple as connecting the correct data to the correct applications. In cases like this, DataHive will recommend a basic data integration and connection process rather than a Big Data implementation. The goal is to use the correct business intelligence and analytic tools and not to simply add Big Data tools for its own sake.

At the same time, there are specific challenges to Social Big Data as well. Companies trying to gain value from the full Twitter firehose need to have semantic strategies, sentiment tracking capabilities, focused goals, and a strong knowledge of which Twitter fields are more likely or less likely to provide value to those goals. Video analysis may require packet inspection, natural language processing, metadata creation and analysis, video surveillance, and user participation tools to translate gigabytes of video sharing into actual insight. These social data sources are much more complicated than the relational databases and structured data marts that DBAs initially grew up with. When we conduct data-driven work, it is in light of Social Big Data for Human Insight.

“Human Insight” is the most important part of this model. DataHive is not concerned with data analysis for its own sake. In fact, one of our biggest criticisms of the “Big Data” mentality is concept that the supposed “data scientist” would look at data without hypotheses and look for findings. (We know that not all data scientists take this approach by any means, but we believe in an empirical and scientific approach for analyzing data.) In our world, businesses and organizations have specific goals that they are trying to achieve and Social Big Data needs to help them to improve processes, provide guidance, and foment disruptive innovation.

Although social media is typically in the hands of marketing or customer service, DataHive believes that there are Human Insights that go across the entire organization: human resources, sales, research, operations, IT. The insight may be a simple as picking up website complaints which lead to the realization that the corporate WAN is being impaired at a key node. From an HR recruiting and morale perspective, the sentiment for your organization may be much stronger or weaker online than your internal metrics may track. And the pure insight and educational value of key thought leaders online can provide value to every level of the organization if the correct information is used.

But beyond the sentiment of the social media itself is another level of insight held through metadata, social connections, and context provided through sales, talent, and other key business capabilities. Data has a topology and a specific meaning, especially as we try to collaborate together. Social efforts can be pointless if we are not talking to the right people or if we lack a critical mass of users. There is also a bigger world of human insight associated with global challenges, but we are starting with business challenges. Today, businesses, tomorrow, the world!

As we look at human insight, we want to show you how to gain value from all three of these areas both in isolation and in combination. We use our decades of experience in using social media, our use of metadata and relational data, our social science backgrounds in understanding the sentiment and psychology of social data, and our business backgrounds to provide you with greater insight into using social data.

If you have questions on what social data is or how to take optimal advantage of your social data, we would love to discuss your social strategy and social data use cases. Please contact us at to schedule a free consultation.

My Introduction to Enterprise Software at IBM Connect 2014

I’m a social consumer technologist. My daily routine includes Twitter, Facebook, Instagram, Flickr, Pinterest, Tumblr, Pinboard, and a fistful of other social and collaborative information-gathering tools; some of these, I use on their own (such as Pinterest), others, I manage through HootSuite, an integrated social media tool. I’ve spent little time working with enterprise-level tools and companies larger than “medium.” So I was intrigued by the opportunity to be introduced to an enterprise social software, IBM Connections, at Connect 2014, and to compare it to the consumer and SMB environments that I was accustomed to working with.

The common ground between enterprise and SMB companies is that they are all aware that they need to be doing social media now. The enterprise is waking up to the fact that social is something the majority of their employees do anyway – and that there needs to be attention given to the policies surrounding that, and that this applies across all strata in a given company – as far down as front-line, and as far up as C-level officers. The attention IBM is giving to design and its Designcamp is a pertinent example to demonstrate a pervasive business initiative, since Designcamp has been deemed so important across IBM that even C-level officers are attending to ensure everyone in the company’s on the same page. A similar initiative for external social at IBM offices could yield similarly intriguing results.

IBM Connections will be significantly easier to learn if it heads in the direction of Mail Next, announced at IBM Connect, via a similar IBM Designcamp initiative. The Mail Next dashboard is where software design has been headed for awhile – being able to see the most important things up front is better than having to dive through layers of nested contextual menus to find it. (Granted, simplification for comprehension vs. options for power users is an ongoing tension.) I found myself in the weeds a fair bit trying to absorb as much as I could regarding IBM’s existing software, but Mail Next stood out as something more modern and easy to grok.

However, some stark differences also showed up in comparing enterprise and SMB social. When you join an enterprise, there’s traditionally not a lot of sanctioned opportunity to bring your own tools. So whatever you have used at home may be very different from what you get to use in an enterprise, and frequently, enterprise tools are so complex that lengthy training sessions are recommended for their effective use. I’ve tested a large number of consumer tools, both for my workflow and for others’, and the ones that remained useful over the long term typically had a combination of great software design, concise demonstrations or explanations, and benefits so obvious that it motivated me to keep using them. If something felt too complex, it was hard to motivate myself to keep up with using the tools. Bridget van Kralingen, SVP of IBM Global Business Services, pointed out that 50% of employees would pay for better and more collaborative tools. This is revelatory.

At this point, businesses small and large need to have a social presence; it’s expected, and this point was made across the board at Connect 2014. IBM certainly knows the importance of social; they encouraged everyone to tweet and post Instagram photos (and IBM applied appropriate gamification throughout the show for fun and glory). But IBM’s software mostly doesn’t reflect that connection yet; it’s so focused on “internal social,” with “external social” feeling somewhat bolted on. Even though they mentioned that you could invite your partners and clients to participate in your internal social spaces, overall, most of the software came off as IBM-social-centric, when smaller businesses are accustomed to sorting out what types of social initiatives go in varying spaces.

The division between “internal” and “external” social isn’t nearly so vast outside the enterprise world. It’s why the IBM-HootSuite partnership will be intriguing to watch – 80 different social networks are already integrated into HootSuite, allowing you to participate in external social both as a reader and a writer. That’s a lot of third-party social integration! IBM Connections, on the other hand, is just starting to integrate third-party social, and so far, primarily as a means to bring external social data into Connections.

So despite the way social is divided into “internal” and “external” for large enterprises, there’s still a lot of common ground between SMB social and enterprise social, particularly with regards to social being a necessity for all businesses at this point. And Mail Next proves that enterprise social software doesn’t have to be complex nests of menu options to be powerful, yet easy to understand, like the most popular consumer social software out there today. I look forward to IBM Design working its way through the rest of IBM’s software; it’s key for making IBM software easier to learn and close the usability gaps between consumer and enterprise software.

The DataHive on Apache Hive

Hive is a terrific Big Data tool
Regular Apis Flores Nest Closeup image courtesy of The Beehive, Oxford | Maths in the City.

As DataHive Consulting, we have been remiss in not mentioning anything about Hive up until now, especially since we think Hive is the easiest way to start using Hadoop for those just starting to make the jump from structured to unstructured data. For those just starting to look into Big Data, Apache Hive is a data warehouse software built on top of Hadoop, which supports the management, querying, and analysis of distributed datasets. It includes ETL (extract-load-transfer) tools, MapReduce-based queries, metadata storage, and indexing. But most importantly, it can all be managed through HiveQL, a query language similar to SQL. Although it lacks full ACID functionality at this point, Hive is a quick way to use Hadoop for those who have SQL and/or MapReduce framework experience.

Here’s a couple of our favorite starting points for learning more about Hive:

Where are you picking up your Hive tips? Please feel free to share in the comments!