Even at the time of hiring, workforce analysis influences from starting i.e. creation of a job description and worker roles, till the recruitment of the person with better chances to succeed in the organization. Through the analysis, companies can make better hiring choices and monitoring the performance in real time. This will help companies to refine their organizational structure and develop talent and leadership within the organization. Workforce analysis will also help in reducing legal claims issues. These all will contribute in cost reduction and smooth working of the organization. Read more at: http://www.smartdatacollective.com/sarah-smith/358073/control-business-costs-workforce-analytics

Michele Goetz of Forrester says, "Seems that the expectations that CRM systems could provide a single trusted view of the customer was starting to hit a reality check." Data quality issues affect 91% of businesses according to a research. There are a few ways to improve your data quality in CRM records. They are: Data Deduplication, Standardize Data Collected, Examine Data Collection Process, and Run Data Quality Initiatives Frequently. Read more at: http://it.toolbox.com/blogs/insidecrm/how-to-improve-the-data-quality-of-crm-records-69748

Data quality has not been so good so far. Huge amount of data can be found that is incorrect or duplicated. It is very difficult to setup an improvement program. One should know what kind of errors are there to allocate the correct resource. To solve data quality problems complex and strategic approach is required which is not same for all problems. Most of the company's decisions are taken after analyzing the data of the company, but if data quality is poor then the result of the decisions can led the company to suffer huge losses. Detecting the data quality is very important because it is positively correlated with business efficiency. Read more at:http://www.smartdatacollective.com/martindoyle/335289/defining-your-data-quality-problems

Financial managers find it very difficult to reconcile goods received against invoices not received. This issues called 'GR-NI' is time consuming to manage. The problem hence gets reduced to lowest of the priorities and leads to increase of financial liabilities and risk for the business. Without proper automation to monitor the discrepancies, paperwork gets piled up which leads to supplier connections suffering and credits being misused. However, with software based supplier reconciliation process in place, the organization can get rid of this huge task and also improve its audit processes solving several risk issues as they arise. A simple overview of the new 'GR-NI' process says that creation of a database with financial and orders data is to be integrated followed by different other steps. The key elements of this solution are methods to get statements directly into the system regardless of format and source and many others. To maximize the value, operational areas should be looked into that can benefit from better processes. Read more at: http://www.smartdatacollective.com/keith-peterson/329860/using-procurement-analytics-simplify-your-supplier-reconciliation

Today marketers know how to enhance customer experience and implement new strategies to attract new customers. Big data, social media marketing and customer relations have influenced the marketing behavior. There will be no insights without data. But by managing data and analyzing it will lead to achieving marketing goals. Analysis of data should be such that it provides helpful conclusion to businesses to make strategies and reach goals. Documentation of business objectives helps business to know what type of data is required and how to manage data. Data should be integrated and structured in such a way that it is reliable to customers. Data validation is required to check the validity of data.   Read more at: http://www.smartdatacollective.com/lbedgood/332008/ultimate-beginner-s-guide-data-quality-and-business-intelligence

Data is the most crucial component of every organization but lately some businesses have started to deal in data. Therefore we need to focus on some basic steps before we begin to trade data and they are as follows:

1. Selling and Accumulating data - Companies that are engaged in selling data have suffered from serious adverse criticisms. If an organization has more data, then it has to bear higher risks and management costs.

2. Making Sense - Big data improves business efficiency and has assisted in the Internet of Things but management costs have to compensate against the money made.

3. Making Money - Organizations search for suitable techniques to create money from data.

4. Risks and Returns - Data helps to improve the quality despite of the risk aspects associated with it.

Read more at: http://www.business2community.com/big-data/can-businesses-profit-data-quality-01275752

Companies of every shape or size recently have moved to Big Data as they realized how beneficial it is for their organizations. To efficiently use the big data, companies need to collect and process it first, from multiple sources. Some data remains unused in the case of unstructured data mostly, which poses a problem later leading to clogging up data centres. Such unused data has been termed as – Dark Data which needs to be cleaned up or else it increases security risk and costs for the companies. Dark Data firstly needs to be identified. It is the information collected but not put to any specific use. Such data remains unused for years and takes up a lot of space which could have been used otherwise to store useful data. Dark Data remains unprotected for a while and poses risk of security breaches and mishaps. Dark Data is costly and dangerous but still companies keep them to make sure they don't lose any kind of records. Cleaning of Dark Data is time consuming but is important as well. One of the most effective ways of avoiding such data is by filtering the data which prevents data from piling up. Other ways to clean such data is by moving the Dark Data to different repositories using cloud computing. Dark Data can be deadly for organizations and hence it should be avoided before it poses any problem for the business.

 Read more at:  http://www.smartdatacollective.com/rick-delgado/323706/importance-cleaning-your-dark-data

Starting off as a small time entrepreneur it might be difficult to see the use of Big Data for your company’s growth. After all Big Data seems to be a term befitting multi million dollars firms, not for start-ups. In reality this isn’t true. Your small start-up can grow exponentially at a affordable cost using data resources which can be availed online by almost anyone.
Here are a couple of ways how it can work for you.
Customer Relationship Management (CRM):
A very important resource for any business is CRM software. Owners can set up a simple CRM spreadsheet, even if it’s just one single webpage, lets you to grab your customer’s feedback which helps towards your company’s growth.
Marketing:
As a small business owner you cannot afford to waste your valuable resources on a  misplaced advertisement or trying to market your product when there is no demand for it. You can use Big Data to analyze the market trends to key in on when and where buying habits are highest.
Big Data is everywhere and you can make use of it easily as long as you keep it simple & streamlined and not overdo it.

Read more at: http://www.smartdatacollective.com/keithtullyy/322521/how-small-business-can-use-big-data

According to Experian’s Data Advantage Report it was found that more than 99 percent of organizations had a plan, but 94 percent still had data errors. The reason for this is bad data quality. Data quality initiatives require investment. Cutting costs is not a solution. The report also found that 27 per cent of businesses are using manual database editing to tackle data quality. But, if data quality software is used, it automatically catches new data problems at the input stage before they are dedicated to a customer relationship management system (CRM). It also detect and remove the duplicates that already exist. This in turn cut down on the manual import and export operations and business moves towards a solution. Read more at: http://it.toolbox.com/blogs/insidecrm/how-to-win-the-crm-data-quality-battle-64966

According to a report by Gartner, analysts estimate that poor data quality is costing organizations on average £9 million annually. Another report by CIO tells us that organizations should be not only protect data but also ensure its quality. Organizations should be aware of bad data. So, to know about how to trust data quality, follow the article written by Peter Walker (Country Manager UKI, Information Builders) at: : http://digitalmarketingmagazine.co.uk/digital-marketing-data/is-your-data-quality-suspect/1132